Big Data and Smart Grid Security
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This assignment delves into the intersection of big data and smart grid security. It analyzes the unique challenges posed by big data's volume, velocity, and variety to smart grid systems. The document further explores various analytical methods used to manage and secure big data in this context, along with a review of relevant technological solutions.
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Full Name
Student ID
Subject ITC571 – Emerging Technology and Innovations
Assignment No Final Report
Due Date
Lecturer’s Name
Your Title Here
Your Name
Your Email
School of Computing and Mathematics, Charles Sturt University, Melbourne, Victoria
1
Student ID
Subject ITC571 – Emerging Technology and Innovations
Assignment No Final Report
Due Date
Lecturer’s Name
Your Title Here
Your Name
Your Email
School of Computing and Mathematics, Charles Sturt University, Melbourne, Victoria
1
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Abstract
Data security and privacy protection are most important for cloud computing technologies.
Cloud computing is the new internet based technologies that can change the world from place to
place us. Now a days the peoples are moving their data to the cloud. If the data is too larger, then
it needs to be access from many other devices. Hence the storage of data in the cloud is more
importent.There are many possibilities for misusage of data without the knowledge of user. The
secured information is mainly affected by the issues like virus and hackers. So the data security
is necessary for many applications and it is very crucial. The main aim of this report is to discuss
the attacks in security for different corporate organizations.
Figure: Graphical Abstract
2
Data security and privacy protection are most important for cloud computing technologies.
Cloud computing is the new internet based technologies that can change the world from place to
place us. Now a days the peoples are moving their data to the cloud. If the data is too larger, then
it needs to be access from many other devices. Hence the storage of data in the cloud is more
importent.There are many possibilities for misusage of data without the knowledge of user. The
secured information is mainly affected by the issues like virus and hackers. So the data security
is necessary for many applications and it is very crucial. The main aim of this report is to discuss
the attacks in security for different corporate organizations.
Figure: Graphical Abstract
2
Table of Contents
1. Introduction.......................................................................................................................................4
Background............................................................................................................................................4
Research significance............................................................................................................................5
Research gap..........................................................................................................................................5
Research aim and objective..................................................................................................................6
Literature review...................................................................................................................................6
2. Materials and methods...................................................................................................................13
3. Results..............................................................................................................................................21
4. Discussion section............................................................................................................................22
5. Conclusion.......................................................................................................................................22
References................................................................................................................................................23
3
1. Introduction.......................................................................................................................................4
Background............................................................................................................................................4
Research significance............................................................................................................................5
Research gap..........................................................................................................................................5
Research aim and objective..................................................................................................................6
Literature review...................................................................................................................................6
2. Materials and methods...................................................................................................................13
3. Results..............................................................................................................................................21
4. Discussion section............................................................................................................................22
5. Conclusion.......................................................................................................................................22
References................................................................................................................................................23
3
1. Introduction
In any organization data security is the main foundation for any field. In the fog system the
data stored for every second and it can be generated by the corporate organizations. Data security is
more and more important in cloud computing processing. The proper cloud storage system is lacked
in many companies. Because the data is in secured. Cloud computing provides easy and
customizable services to the users for various cloud applications. The data will be risk at if the
security is not provided properly for transmission of data and its operations. The cloud computing is
needed by the different corporate network organizations due to the need for the plentiful properties
to be used in great demand and the lack of properties. The lesser and medium corporate network
organizations are moved to the cloud computing technologies. Because the cloud computing is not
only provides the technical solution of data security but it can also provide the professional model
for many organizations. Most of the organizations are focus on their professional process for in
order to increase the corporation profits. The accessibility and the retrieval of extremely efficient
data is offered by the cloud computing technology. The obligation of resource optimization is
provided by the cloud method. Now a days the security is the big challenge for most of the
corporate organizations and other fields due to the wide range of alteration.
Background
The number of privacy and security is developed by the collection of data .collection of data
is also referred to as the Big data. In all over the world privacy is the most important concern in the
various investigations. Cloud computing is the most advanced technology for document storage
based platforms. The data to be stored and the cloud data is accessed from anywhere by using cloud
computing applications. The important use of cloud is to decrease more amount of information like
storage of data, investigation purposes, handling of information. Hence more technical advanced
technologies are intended with more confidential and it takes challenging risks. Cloud computing is
provide the fast developing storage for security of data. The privacy security and data security are
the most important issues in cloud computing architecture. The both issues are related to the
software and hardware of cloud computing applications. In big data analysis the cloud computing
have been implemented in both industry applications and academic applications. The security is
more important analysis in cloud computing. This analysis is mainly provides the different services,
controls to protection of data and infrastructure.
4
In any organization data security is the main foundation for any field. In the fog system the
data stored for every second and it can be generated by the corporate organizations. Data security is
more and more important in cloud computing processing. The proper cloud storage system is lacked
in many companies. Because the data is in secured. Cloud computing provides easy and
customizable services to the users for various cloud applications. The data will be risk at if the
security is not provided properly for transmission of data and its operations. The cloud computing is
needed by the different corporate network organizations due to the need for the plentiful properties
to be used in great demand and the lack of properties. The lesser and medium corporate network
organizations are moved to the cloud computing technologies. Because the cloud computing is not
only provides the technical solution of data security but it can also provide the professional model
for many organizations. Most of the organizations are focus on their professional process for in
order to increase the corporation profits. The accessibility and the retrieval of extremely efficient
data is offered by the cloud computing technology. The obligation of resource optimization is
provided by the cloud method. Now a days the security is the big challenge for most of the
corporate organizations and other fields due to the wide range of alteration.
Background
The number of privacy and security is developed by the collection of data .collection of data
is also referred to as the Big data. In all over the world privacy is the most important concern in the
various investigations. Cloud computing is the most advanced technology for document storage
based platforms. The data to be stored and the cloud data is accessed from anywhere by using cloud
computing applications. The important use of cloud is to decrease more amount of information like
storage of data, investigation purposes, handling of information. Hence more technical advanced
technologies are intended with more confidential and it takes challenging risks. Cloud computing is
provide the fast developing storage for security of data. The privacy security and data security are
the most important issues in cloud computing architecture. The both issues are related to the
software and hardware of cloud computing applications. In big data analysis the cloud computing
have been implemented in both industry applications and academic applications. The security is
more important analysis in cloud computing. This analysis is mainly provides the different services,
controls to protection of data and infrastructure.
4
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Research significance
The information and the data files stored in the system is easily damaged by the computer
virus. Many organization and industry stores their data in the computer that is lost by the
computer virus. the computer virus are entered into system through many ways such as copying
files from some computers, download the data or information from internet and download the
application from the internet. Sometimes the mobile phones data also damaged by virus. The
computer virus are Boot sector virus, Direct Action Virus, Resident virus, space filler virus,
polymorphic virus, multipartite virus and overwrite virus. If the system has virus, then it has
some problems. The problems are Pop-ups, crashing, computer slows down, hard Drive
malfunction, Slow startup, Printer issues, affected applications, antivirus sites blocked, gibberish
dialog box, unusual network security, running out of storage space, sending strange messages
Automatically, disabled security solution, appearance of error messages, sent mails, computer
malfunction hardware and accessory problems.to avoid the loss of computer and mobile data,
some antivirus software are installed in the device. The antivirus software are AVG, Kaspersky,
K7 and Avast etc.
Research gap
The emerging technology limitations are relevant to the followings
It make more challenge to collect and manage much amount of information.
For reliability and data analytics, it requires big data development and management.
The real time and scalability requirements are challenged.
The Big Data are integrated into the cloud computing.
The advanced algorithms are not used. Because it has many advantages.
Previous technologies needs many chips and sensors.
The technologies don’t use advanced security and software up gradation.
In mobility fog and cloud computing, the confidentiality and security made more
challenges.
It made the very difficult process to remove the data, files and images etc. in the internet.
It helps to theft for identifying the user data, if the user is not protect their virtual image.
It is difficult to teach, because student provide their attention in the internet.
To adapt the black swan events.
5
The information and the data files stored in the system is easily damaged by the computer
virus. Many organization and industry stores their data in the computer that is lost by the
computer virus. the computer virus are entered into system through many ways such as copying
files from some computers, download the data or information from internet and download the
application from the internet. Sometimes the mobile phones data also damaged by virus. The
computer virus are Boot sector virus, Direct Action Virus, Resident virus, space filler virus,
polymorphic virus, multipartite virus and overwrite virus. If the system has virus, then it has
some problems. The problems are Pop-ups, crashing, computer slows down, hard Drive
malfunction, Slow startup, Printer issues, affected applications, antivirus sites blocked, gibberish
dialog box, unusual network security, running out of storage space, sending strange messages
Automatically, disabled security solution, appearance of error messages, sent mails, computer
malfunction hardware and accessory problems.to avoid the loss of computer and mobile data,
some antivirus software are installed in the device. The antivirus software are AVG, Kaspersky,
K7 and Avast etc.
Research gap
The emerging technology limitations are relevant to the followings
It make more challenge to collect and manage much amount of information.
For reliability and data analytics, it requires big data development and management.
The real time and scalability requirements are challenged.
The Big Data are integrated into the cloud computing.
The advanced algorithms are not used. Because it has many advantages.
Previous technologies needs many chips and sensors.
The technologies don’t use advanced security and software up gradation.
In mobility fog and cloud computing, the confidentiality and security made more
challenges.
It made the very difficult process to remove the data, files and images etc. in the internet.
It helps to theft for identifying the user data, if the user is not protect their virtual image.
It is difficult to teach, because student provide their attention in the internet.
To adapt the black swan events.
5
To take global entrepreneurship.
To compete through blue ocean strategy with agile start-up methodologies.
To maximize the connection of globalization.
To increase the customer choices and expectations.
To change the workplace trends and dynamics.
To Advances the technology.
Research aim and objective
In the advanced technologies the security and stability is necessary to increase for the safety
purpose. Security attacks in the many organizations network investigation is the main aim of this
research. The main of this research is to update the anti-virus in the systems and improve the
security for the advanced technologies.
The main analysis is fully based on real time processing applications, The real time
problems are faced by the different organizations are showed by using different existing research
analysis. The implementation of accuracy of data and prevention of data hacking will be done by
using the clustering algorithm. To analyses the security in many corporate networks in different
field is the main objective for this report. To find the correct solution for the different issues faced
by the different corporate networks.
Literature review
The author described in that [1], the Universal Serial Bus (USB) has security risks in the
system. The USB operated at U3 technology. It made more interest to user, for accessing the
hacking tools. The malware scanners are used for solving the hacking tools. The USB is acted as
hacking tool for cell phones. Many technologies are used for hacking information from the
mobile phone with the help of USB. The working principle of USB and U3 portable applications
are analyzed. The portable hacking tools are created by attackers with the help of USB and U3
techniques. The detailed solution for reducing the threat in the enterprise administrators is
provided.
6
To compete through blue ocean strategy with agile start-up methodologies.
To maximize the connection of globalization.
To increase the customer choices and expectations.
To change the workplace trends and dynamics.
To Advances the technology.
Research aim and objective
In the advanced technologies the security and stability is necessary to increase for the safety
purpose. Security attacks in the many organizations network investigation is the main aim of this
research. The main of this research is to update the anti-virus in the systems and improve the
security for the advanced technologies.
The main analysis is fully based on real time processing applications, The real time
problems are faced by the different organizations are showed by using different existing research
analysis. The implementation of accuracy of data and prevention of data hacking will be done by
using the clustering algorithm. To analyses the security in many corporate networks in different
field is the main objective for this report. To find the correct solution for the different issues faced
by the different corporate networks.
Literature review
The author described in that [1], the Universal Serial Bus (USB) has security risks in the
system. The USB operated at U3 technology. It made more interest to user, for accessing the
hacking tools. The malware scanners are used for solving the hacking tools. The USB is acted as
hacking tool for cell phones. Many technologies are used for hacking information from the
mobile phone with the help of USB. The working principle of USB and U3 portable applications
are analyzed. The portable hacking tools are created by attackers with the help of USB and U3
techniques. The detailed solution for reducing the threat in the enterprise administrators is
provided.
6
According to the [2], virus, Trojan horses and worms are security issues, encountered at
resent research. These security issues are based on the USB technology hack tools. In host
computers, the hackers are entered directly.to reduce the threats in the hacking tools and malware
on USB devices, the windows operating system features are used. There is no need for complex
configuration and costly software license, to make the solution for hacking. The script packages
are used to solve the complex process in the hacking. It is very helpful for both home and office
computer users. This solution does not remove the inactivated malware in the USB devices.
As per [3], The USB device in the system or mobile phone made more security issues to
users. It affected the information and data in the system. It is a large issue in the whole system.
The multi payload hacking tools are investigated in the paper. The USB is one of the open
standard technology. The open standard technology used in the USB are embedded software and
universal serial bus drivers. The attacks of the system is identified and taxonomy of attacks are
investigated by the open standard technology. The security frame work is created for solving the
USB software attack in the base of newer windows operating system.
As per the research paper [4], the author state that the company sustainability and its growth,
the negative impact is occurred in the analytical tools. This is done because of the competitive
market. In this paper using computer algebra systems the performance of big data is analyzed. The
open source tools of Jasper soft and pentaho is analyzed. The comparison between these two tools is
conducted by the author. In this paper, main target is given to the extract transform and Load. The
jasper soft tool is having more CPU processing time in the result if extract transform and load. In
the case of Pentaho tool results are shows in terms of performance metrics.
The performance measurement is denoted by 42.28%.Hence, this research paper provides
the guidelines for various many researchers. And it also provides the bid data processing in IT
professionals. This research paper also used for open source tool implementation process. The
author mainly highlights the business intelligence tools and big data analysis in this research paper.
The author described in that [5], the data analysis is conducted based on the review work.
The algorithm for the data wrangling is implemented for analyzing the big data. The data
wrangling algorithm is used for many applications such as topological data, textual data,
government data, educational data, galaxy data, financial data and medical data. Instead of using
the data wrangling algorithm for medical data application, the clustering algorithm is preferred.
7
resent research. These security issues are based on the USB technology hack tools. In host
computers, the hackers are entered directly.to reduce the threats in the hacking tools and malware
on USB devices, the windows operating system features are used. There is no need for complex
configuration and costly software license, to make the solution for hacking. The script packages
are used to solve the complex process in the hacking. It is very helpful for both home and office
computer users. This solution does not remove the inactivated malware in the USB devices.
As per [3], The USB device in the system or mobile phone made more security issues to
users. It affected the information and data in the system. It is a large issue in the whole system.
The multi payload hacking tools are investigated in the paper. The USB is one of the open
standard technology. The open standard technology used in the USB are embedded software and
universal serial bus drivers. The attacks of the system is identified and taxonomy of attacks are
investigated by the open standard technology. The security frame work is created for solving the
USB software attack in the base of newer windows operating system.
As per the research paper [4], the author state that the company sustainability and its growth,
the negative impact is occurred in the analytical tools. This is done because of the competitive
market. In this paper using computer algebra systems the performance of big data is analyzed. The
open source tools of Jasper soft and pentaho is analyzed. The comparison between these two tools is
conducted by the author. In this paper, main target is given to the extract transform and Load. The
jasper soft tool is having more CPU processing time in the result if extract transform and load. In
the case of Pentaho tool results are shows in terms of performance metrics.
The performance measurement is denoted by 42.28%.Hence, this research paper provides
the guidelines for various many researchers. And it also provides the bid data processing in IT
professionals. This research paper also used for open source tool implementation process. The
author mainly highlights the business intelligence tools and big data analysis in this research paper.
The author described in that [5], the data analysis is conducted based on the review work.
The algorithm for the data wrangling is implemented for analyzing the big data. The data
wrangling algorithm is used for many applications such as topological data, textual data,
government data, educational data, galaxy data, financial data and medical data. Instead of using
the data wrangling algorithm for medical data application, the clustering algorithm is preferred.
7
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Because the clustering algorithm is very useful for medical data application compared to the data
wrangling algorithm.
According to [6], the author explained the data analysis of data retrieved from scientific
publications that defines the applied algorithm models for data wrangling in big data. This
method evaluates and discovers applied algorithm models of data applications in area of big data
in data wrangling methods. The data wrangling defines complex data by procedure of planning,
which includes grouping and clusters of intricate data set in order to access trending themes. The
medical files used for the clustering algorithm for data wrangling purposes in best of research
papers, i.e., 5 medical files presentations out of 8 medical files applications are used the
clustering algorithm. The file applications are analyzed for this discussion were splitted into two
algorithms. The greatest frequency of the data presentation used in the investigation papers is
gathered according to algorithms used for data wrangling determinations. The data wrangling
algorithm used in various data application such as textual data, topological data, galaxy data,
medical data, financial data, educational science and governmental data, etc. which could use
certain methods for clustering that are very easier when compared to others. Finally the author
concluded that, collecting number of data in order to achieve the greatest accuracy in the results
found.
According to [7], the author describes that, discovers the Hypothesis of a computer virus
risk and how damaging it will be if implemented on a target device. They explains analysis from
the extraction of data from various test of states and session conducted in a test location. The
results shows that, proper security execution and the use of recent OS patches and anti-virus
programs helps to prevent the data loss and any type viral threat on the computer system. The
author concluded that, the possible solution which can help other persons to prevent their
computer system from the type of damages. The author could measure that can’t test all the
possible system virus and other type malicious code to retrieve the possible source code.
According to [8], the author states that, the big data have a rising number of security and
privacy issues. A New technology without doubt transports people benefits, rights, suitability
and competences. At that time, technical advances are attended with threats which can pose
hazardous confidentiality risks. Confidentiality of data is a basis of more concern to investigators
through the world. The main objectives is to find various security problems of big data in
8
wrangling algorithm.
According to [6], the author explained the data analysis of data retrieved from scientific
publications that defines the applied algorithm models for data wrangling in big data. This
method evaluates and discovers applied algorithm models of data applications in area of big data
in data wrangling methods. The data wrangling defines complex data by procedure of planning,
which includes grouping and clusters of intricate data set in order to access trending themes. The
medical files used for the clustering algorithm for data wrangling purposes in best of research
papers, i.e., 5 medical files presentations out of 8 medical files applications are used the
clustering algorithm. The file applications are analyzed for this discussion were splitted into two
algorithms. The greatest frequency of the data presentation used in the investigation papers is
gathered according to algorithms used for data wrangling determinations. The data wrangling
algorithm used in various data application such as textual data, topological data, galaxy data,
medical data, financial data, educational science and governmental data, etc. which could use
certain methods for clustering that are very easier when compared to others. Finally the author
concluded that, collecting number of data in order to achieve the greatest accuracy in the results
found.
According to [7], the author describes that, discovers the Hypothesis of a computer virus
risk and how damaging it will be if implemented on a target device. They explains analysis from
the extraction of data from various test of states and session conducted in a test location. The
results shows that, proper security execution and the use of recent OS patches and anti-virus
programs helps to prevent the data loss and any type viral threat on the computer system. The
author concluded that, the possible solution which can help other persons to prevent their
computer system from the type of damages. The author could measure that can’t test all the
possible system virus and other type malicious code to retrieve the possible source code.
According to [8], the author states that, the big data have a rising number of security and
privacy issues. A New technology without doubt transports people benefits, rights, suitability
and competences. At that time, technical advances are attended with threats which can pose
hazardous confidentiality risks. Confidentiality of data is a basis of more concern to investigators
through the world. The main objectives is to find various security problems of big data in
8
numerous areas and provides solution by evaluating results. The outcomes of the content
investigation propose that the financial institutions and internet applications are deals with exact
security problems, while social media and other businesses are deals with privacy issues of
complex information that have sensitive privacy concerns. This discussion has addressed gaps by
mentioned security and privacy issues that big businesses face with new technical developments
in company. By estimating these gaps there might be some light outhouse on these problems of
big data and offer future investigator instructions to solve them. For the future, number of data
would be collected to detect the privacy and security challenges of Big Data.
It is stated that [9], the productivity, corporate society and the management of
organization depends on the database. All the organization have outsource their database in the
form of big data and transfer to in cloud. The cloud computing technology introduce many
benefits for company, and security risk issue still remains as a large problem for its wide range
spread adoption. This system have many benefits, security, nonetheless and privacy factors are at
the upper to control complex data, that including number of technologies with cloud computing
such as networking, databases, operating systems, and virtualization that are difficult as
computing is still in the development and would be created on ration of benefits to remove
threats and danger.
As per [10], the enhancement and growth of technology in business society have been led
to records storage and privacy issues. The risk arises from the organization of trillions of data,
processed every seconds in the corporate, which is known as “big data”. The big data required to
store and managed by the greater organization that could not have the correct storage system.
The main objective is to find the solution to this raising problems by analyzing gaps and to
estimate the possible solutions and provide solutions by conflicting Big Data management
methods of No SQL databases; Dynamo DB, Cassandra and Big Table. The system presentations
are analyzed based on their availability, consistency and partition narrowness. The discussion
concluded that Amazon's Dynamo DB and Google's Big Table are also dangerous and well-
organized on their own, and also originate that the grouping of both systems had affected the
growth of Cassandra.
It is stated that [11], the computers have contributed significantly to the purpose of
storage and management of enormous capacities of data. Also, the development of the DBMS
9
investigation propose that the financial institutions and internet applications are deals with exact
security problems, while social media and other businesses are deals with privacy issues of
complex information that have sensitive privacy concerns. This discussion has addressed gaps by
mentioned security and privacy issues that big businesses face with new technical developments
in company. By estimating these gaps there might be some light outhouse on these problems of
big data and offer future investigator instructions to solve them. For the future, number of data
would be collected to detect the privacy and security challenges of Big Data.
It is stated that [9], the productivity, corporate society and the management of
organization depends on the database. All the organization have outsource their database in the
form of big data and transfer to in cloud. The cloud computing technology introduce many
benefits for company, and security risk issue still remains as a large problem for its wide range
spread adoption. This system have many benefits, security, nonetheless and privacy factors are at
the upper to control complex data, that including number of technologies with cloud computing
such as networking, databases, operating systems, and virtualization that are difficult as
computing is still in the development and would be created on ration of benefits to remove
threats and danger.
As per [10], the enhancement and growth of technology in business society have been led
to records storage and privacy issues. The risk arises from the organization of trillions of data,
processed every seconds in the corporate, which is known as “big data”. The big data required to
store and managed by the greater organization that could not have the correct storage system.
The main objective is to find the solution to this raising problems by analyzing gaps and to
estimate the possible solutions and provide solutions by conflicting Big Data management
methods of No SQL databases; Dynamo DB, Cassandra and Big Table. The system presentations
are analyzed based on their availability, consistency and partition narrowness. The discussion
concluded that Amazon's Dynamo DB and Google's Big Table are also dangerous and well-
organized on their own, and also originate that the grouping of both systems had affected the
growth of Cassandra.
It is stated that [11], the computers have contributed significantly to the purpose of
storage and management of enormous capacities of data. Also, the development of the DBMS
9
(Database Management Systems) makes the way to a huge numbers of healthcare or Medical
databases. Altering management and information of significant quantities of various statistics
have turned into an important area of investigation. The method of knowing potentially useful,
accurate, original, and conclusively logical designs in data, is specifically named Data Mining.
This discussion purposes to use classification approaches in the part of medical science and
bioinformatics. The Classification is often normal to a data mining technique, and reside in a set
of classified cases to create an example that can be familiarized to classify the collection of
heavy records. CKD (Chronic kidney disease) is a state that affects slow failure of kidney
function. The essential usefulness of the Kidney is to clean the eradicating wastes and blood
from the human body. Kidney changes the filtered wastes to the removes and bladder it late over
urination. For the field of medical science and bio-informatics accuracy, the important objective
is to agree with complex data and a single error that can lead to a tragedy. Hence, our outcomes
clearly displays that Perception of Multilayer classification technique is the maximum accurate
and most appropriate classification procedure used in the field of medical science and
bioinformatics for additional predictions and data analysis.
As per [12], the author sates that, Internet of Things, remote data centers, and devices are
need to connect. The need of fog is to minimize the quantity of data transferred for analysis and
storage, processing, to increase the process of computing. The gap among, devices and fog
computing technologies necessary to slight down as development in the business relies on the
capability to link to digital channels for producing more quantities of information. The cloud
computing is unrealistic for many IOT applications, so that fog computing is frequently seen as a
feasible alternate. Fog is appropriate for many Internet of Things services as it permitted a wide
collection of benefits, like reduced bandwidth, minimized latency, and improved security. The
author described, we have tried to fill that gap, and mention the areas that essential consideration
in the future. It is evident from the discussed that Fog computing is a still a new part nowadays,
and is still does not well assumed or investigated, even though the important role it is possible to
show in the future.
According to [13], the author states that, Fast-growing effective document storage stages
provide facilities with least expense in the business society. The Cloud computing provide a
solution for this issue for corporate and hospital owners as it expels the needs of provisioning
10
databases. Altering management and information of significant quantities of various statistics
have turned into an important area of investigation. The method of knowing potentially useful,
accurate, original, and conclusively logical designs in data, is specifically named Data Mining.
This discussion purposes to use classification approaches in the part of medical science and
bioinformatics. The Classification is often normal to a data mining technique, and reside in a set
of classified cases to create an example that can be familiarized to classify the collection of
heavy records. CKD (Chronic kidney disease) is a state that affects slow failure of kidney
function. The essential usefulness of the Kidney is to clean the eradicating wastes and blood
from the human body. Kidney changes the filtered wastes to the removes and bladder it late over
urination. For the field of medical science and bio-informatics accuracy, the important objective
is to agree with complex data and a single error that can lead to a tragedy. Hence, our outcomes
clearly displays that Perception of Multilayer classification technique is the maximum accurate
and most appropriate classification procedure used in the field of medical science and
bioinformatics for additional predictions and data analysis.
As per [12], the author sates that, Internet of Things, remote data centers, and devices are
need to connect. The need of fog is to minimize the quantity of data transferred for analysis and
storage, processing, to increase the process of computing. The gap among, devices and fog
computing technologies necessary to slight down as development in the business relies on the
capability to link to digital channels for producing more quantities of information. The cloud
computing is unrealistic for many IOT applications, so that fog computing is frequently seen as a
feasible alternate. Fog is appropriate for many Internet of Things services as it permitted a wide
collection of benefits, like reduced bandwidth, minimized latency, and improved security. The
author described, we have tried to fill that gap, and mention the areas that essential consideration
in the future. It is evident from the discussed that Fog computing is a still a new part nowadays,
and is still does not well assumed or investigated, even though the important role it is possible to
show in the future.
According to [13], the author states that, Fast-growing effective document storage stages
provide facilities with least expense in the business society. The Cloud computing provide a
solution for this issue for corporate and hospital owners as it expels the needs of provisioning
10
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planning, and permits companies to development their filling scheme according to the service
demands. The Medical follows seriously, rely on file storage as; almost all the necessary
information listed in medical files are kept in a printed layout. This discussion recommends that
the above planned proposals has been create by this contented that will helps to raise the quality
of medical information and improve health information scheme and unintentionally influence
their storage systems. The removal, containment and privacy of medical accounts need to be
continued in order to play with the rising demands and challenges.
According to the [14], The Big data techniques are analyzed in the form of comparative
type of analysis for many companies. The Big data techniques in this paper provided the
information of social media like Google, Twitter, FB and amazon. The data ware house approach
is needed for these companies. The information about the differentiation of transaction methods
and dare ware house storages are known to the Google. The information transition in the face
book is done based on the prediction system programming language. The prediction system is
cascade based. Twitter has no limit for data transition. So it needs system setup.
According to [15], the author describe that, the weak radiofrequency emission exposure
from the phone radiation on living plants. The author completed an enquiry of data from 45 peer
revised technical publication explaining 169 investigational observations to notice the
physiological and morphological variations in the plants because of the non-thermal Radio
Frequency-EMF special effects from the mobile radiation. Biological effects of radiation
produced due to electromagnetic from the mobile phone communication systems that may
depends on mean power level, modulation and frequency of the electromagnetic signal. The
main objective is to investigate the theory that non thermal, RF EMFs, weak have a more effect
on living organisms on plants. Our investigation of the reported outcomes demonstrates that
Radio Frequency-EMFs may be effect on plants. According to that, it proposes a possible
advantage of drawing attention to the importance of the exposure restrictions to weak RF-EMFs.
Hence, this description provides a new evidence that can supporting our theory. No one findings
will be directly related with human; however, on the other side, this could not be omitted, as it
may impact the human safety and health, either affect directly or indirectly, due to their
difficulties and varied effects. This theory could be needful as a reference for investigators
11
demands. The Medical follows seriously, rely on file storage as; almost all the necessary
information listed in medical files are kept in a printed layout. This discussion recommends that
the above planned proposals has been create by this contented that will helps to raise the quality
of medical information and improve health information scheme and unintentionally influence
their storage systems. The removal, containment and privacy of medical accounts need to be
continued in order to play with the rising demands and challenges.
According to the [14], The Big data techniques are analyzed in the form of comparative
type of analysis for many companies. The Big data techniques in this paper provided the
information of social media like Google, Twitter, FB and amazon. The data ware house approach
is needed for these companies. The information about the differentiation of transaction methods
and dare ware house storages are known to the Google. The information transition in the face
book is done based on the prediction system programming language. The prediction system is
cascade based. Twitter has no limit for data transition. So it needs system setup.
According to [15], the author describe that, the weak radiofrequency emission exposure
from the phone radiation on living plants. The author completed an enquiry of data from 45 peer
revised technical publication explaining 169 investigational observations to notice the
physiological and morphological variations in the plants because of the non-thermal Radio
Frequency-EMF special effects from the mobile radiation. Biological effects of radiation
produced due to electromagnetic from the mobile phone communication systems that may
depends on mean power level, modulation and frequency of the electromagnetic signal. The
main objective is to investigate the theory that non thermal, RF EMFs, weak have a more effect
on living organisms on plants. Our investigation of the reported outcomes demonstrates that
Radio Frequency-EMFs may be effect on plants. According to that, it proposes a possible
advantage of drawing attention to the importance of the exposure restrictions to weak RF-EMFs.
Hence, this description provides a new evidence that can supporting our theory. No one findings
will be directly related with human; however, on the other side, this could not be omitted, as it
may impact the human safety and health, either affect directly or indirectly, due to their
difficulties and varied effects. This theory could be needful as a reference for investigators
11
managing epidemiological revisions and the long-standing experiments, using an entire
organisms, to detect the effects of Radio Frequency-EMFs.
As per [16], the author states that past flood in India and Australia to observe the
emerging trends and patterns to implements prediction of flood dangers. The two flood hazard
assessment metrics are utilized by the preceding research, is used to clearly understand the
overflow aspects such as Magnitude, (which relates to flood severity, duration and affected zone
of floods), Severity class (which is related with frequency of flood). The factors that affect flood
events are complicated and interconnected. The different weather factors like storm surges, snow
melts from the heavy rain, cyclones, structural failures of dams and insufficient drainage systems
are certain causal factors to recent rise. The author explains the statistical analysis to establish the
data and to compare frequent calculations on one sample to measure whether their population
mean classification differ in the dataset for each and every attributes. The analysis part shows
that small growth in the previous three decades. The twenty fifth–seventy fifth percentile values
displays that there is a little bit higher harshness of flood danger in Australian data when related
to the Indian data. This discussion highlights that the results of analysis could be need for bias
improvement of flood estimate by using data driven models or theoretical. However, this
discussion is much useful for ecological disaster recovery result makers, policy makers, experts,
and other industry specialists to relate and evaluate the potential risks and to clearly understand
the significance of emerging flood extenuation measures.
12
organisms, to detect the effects of Radio Frequency-EMFs.
As per [16], the author states that past flood in India and Australia to observe the
emerging trends and patterns to implements prediction of flood dangers. The two flood hazard
assessment metrics are utilized by the preceding research, is used to clearly understand the
overflow aspects such as Magnitude, (which relates to flood severity, duration and affected zone
of floods), Severity class (which is related with frequency of flood). The factors that affect flood
events are complicated and interconnected. The different weather factors like storm surges, snow
melts from the heavy rain, cyclones, structural failures of dams and insufficient drainage systems
are certain causal factors to recent rise. The author explains the statistical analysis to establish the
data and to compare frequent calculations on one sample to measure whether their population
mean classification differ in the dataset for each and every attributes. The analysis part shows
that small growth in the previous three decades. The twenty fifth–seventy fifth percentile values
displays that there is a little bit higher harshness of flood danger in Australian data when related
to the Indian data. This discussion highlights that the results of analysis could be need for bias
improvement of flood estimate by using data driven models or theoretical. However, this
discussion is much useful for ecological disaster recovery result makers, policy makers, experts,
and other industry specialists to relate and evaluate the potential risks and to clearly understand
the significance of emerging flood extenuation measures.
12
2. Materials and methods
Firstly, the surviving research papers were studied. Next the operation, deliberations, related
solutions, issues are explained. Based on the information collected from the surviving research
papers the research analysis is done and to find the complete solution for the hackers and virus of
safety issues. The data is secured in big data analysis based on data privacy, data management,
infrastructure security, Integrity and reactive security.
13
Firstly, the surviving research papers were studied. Next the operation, deliberations, related
solutions, issues are explained. Based on the information collected from the surviving research
papers the research analysis is done and to find the complete solution for the hackers and virus of
safety issues. The data is secured in big data analysis based on data privacy, data management,
infrastructure security, Integrity and reactive security.
13
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Figure: Graphical Representation
From the above graphical representation diagram, in the big data analysis the data is
secured. But there is some security attacks are takes place. The privacy issues, viruses, Trojan horse
attacks are occurs.
The objective of the research represented by the following table. This approach is
accomplished by based on the author, consideration, data, issues and solutions.
Author Considerations Data Issue solutions
(Harris A Khan, n.
d)
Analysis is based on cyber
security
This method is
mainly used
for virus attack
The main
issue of the
paper attacks
and virus
from the
computer
The detection
is done based
on the
behavior of
antivirus
program
(signature and
heuristic).
14
From the above graphical representation diagram, in the big data analysis the data is
secured. But there is some security attacks are takes place. The privacy issues, viruses, Trojan horse
attacks are occurs.
The objective of the research represented by the following table. This approach is
accomplished by based on the author, consideration, data, issues and solutions.
Author Considerations Data Issue solutions
(Harris A Khan, n.
d)
Analysis is based on cyber
security
This method is
mainly used
for virus attack
The main
issue of the
paper attacks
and virus
from the
computer
The detection
is done based
on the
behavior of
antivirus
program
(signature and
heuristic).
14
(Sushma
Munugala,n. d)
Online information has
reliability, integration is
done in the cloud
computing, optimization
computation is done.
The Dos
attacks,
Encryption,
Quick grid and
exfiltration is
used for
protecting data.
The Big data
is used in
management,
analytics and
medical
organization.
The cloud
computing
increases the
security level.
(Thulara
N.Hewage, 2017)
The data collection
comparison, raw data
analysis.
The collection
of raw data.
The database
is shared in
world wide.
The
techniques of
parallel mode
and sequential
mode are used
in Google file
system. The
technology
hadoop is
used.
(Sultana Kalid, n.
d)
In this, the availability and
scalability are considered.
Google
product based
project of big
table data is
analyzed.
The main
issue of this
paper
requires
primary
server for
handling the
data set.
The system
performance
is high.
(R.A.Jeewantha,20
07)
The performance
evaluation, collection of
data.
Evaluation of
RMS.
The
performance
measure
needs the
different
classifiers for
measurement
s
Instances are
correctly
classified
(Manbir Singh, n.
d)
This is based on security
challenges.
Big data is
based on data
mining, pattern
evaluation and
data
transmission
Real time
issues are
monitored.
For security
purpose the
inner layer of
data is
covered by
the outer
layer. The
protection is
mainly based
on layers.
15
Munugala,n. d)
Online information has
reliability, integration is
done in the cloud
computing, optimization
computation is done.
The Dos
attacks,
Encryption,
Quick grid and
exfiltration is
used for
protecting data.
The Big data
is used in
management,
analytics and
medical
organization.
The cloud
computing
increases the
security level.
(Thulara
N.Hewage, 2017)
The data collection
comparison, raw data
analysis.
The collection
of raw data.
The database
is shared in
world wide.
The
techniques of
parallel mode
and sequential
mode are used
in Google file
system. The
technology
hadoop is
used.
(Sultana Kalid, n.
d)
In this, the availability and
scalability are considered.
product based
project of big
table data is
analyzed.
The main
issue of this
paper
requires
primary
server for
handling the
data set.
The system
performance
is high.
(R.A.Jeewantha,20
07)
The performance
evaluation, collection of
data.
Evaluation of
RMS.
The
performance
measure
needs the
different
classifiers for
measurement
s
Instances are
correctly
classified
(Manbir Singh, n.
d)
This is based on security
challenges.
Big data is
based on data
mining, pattern
evaluation and
data
transmission
Real time
issues are
monitored.
For security
purpose the
inner layer of
data is
covered by
the outer
layer. The
protection is
mainly based
on layers.
15
(Dung V Pham, Ali
Syed, n. d)
The attacks produced
depend on the USB
devices.
the USB uses
the U3
technology
hacking tools
The
information’s
are stolen
from the
system
without any
need of user
and U3.
The U3 based
technology
are switchable
USB and data
recovery
software.
(Dung V
Pham,2010)
The pattern analysis and
user account control is
considered.
The data is
mainly used
for storage of
data in USB
devices
Virus and
hackers of
security
attack are the
main issues
Updating the
anti-malware
systems.
Unsecured
threats are
blocked.
(Binara
N.B Ekanayake, n.
d)
The data processing
analysis
It has different
fog modes.
Efficiency is
less because
the privacy
and security
issues
combined in
the
scalability.
the Rasberry
Pis is
collected by
the
Micro clouds.
(Kamalpreet Kaur,
n. d)
The data protection,
Access control and
management trust is done.
The VLC open
source is
developed.
The different
challenges
are done in
the Cloud
computing.
Data
verification is
perfect.
Dung Vu Pham Information security risks USB storage
device for
attack.
Attackers
easily take
the data from
the system
using USB
drivers.
The security
frame work is
designed for
identifying
software
attack.
Amit Gupta
Crime and accident
reduction.
The many
algorithms are
used for
analyzing.
The Security
agencies and
policy
departments
are worried,
because they
don’t get
correct
information
Data mining
techniques
and tools are
used for
providing the
solution.
16
Syed, n. d)
The attacks produced
depend on the USB
devices.
the USB uses
the U3
technology
hacking tools
The
information’s
are stolen
from the
system
without any
need of user
and U3.
The U3 based
technology
are switchable
USB and data
recovery
software.
(Dung V
Pham,2010)
The pattern analysis and
user account control is
considered.
The data is
mainly used
for storage of
data in USB
devices
Virus and
hackers of
security
attack are the
main issues
Updating the
anti-malware
systems.
Unsecured
threats are
blocked.
(Binara
N.B Ekanayake, n.
d)
The data processing
analysis
It has different
fog modes.
Efficiency is
less because
the privacy
and security
issues
combined in
the
scalability.
the Rasberry
Pis is
collected by
the
Micro clouds.
(Kamalpreet Kaur,
n. d)
The data protection,
Access control and
management trust is done.
The VLC open
source is
developed.
The different
challenges
are done in
the Cloud
computing.
Data
verification is
perfect.
Dung Vu Pham Information security risks USB storage
device for
attack.
Attackers
easily take
the data from
the system
using USB
drivers.
The security
frame work is
designed for
identifying
software
attack.
Amit Gupta
Crime and accident
reduction.
The many
algorithms are
used for
analyzing.
The Security
agencies and
policy
departments
are worried,
because they
don’t get
correct
information
Data mining
techniques
and tools are
used for
providing the
solution.
16
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at correct
time.
Victor M. Parra
Big data Analytical
tools.
Sustainabilit
y and
development
of the
company is
reduced.
Pentaho and
Java J2EE
application is
used in the BI
to improve the
company.
Chiranjivi Bashyal Big data
.
Algorithms are
used for
solving the
problems.
Less
accuracy are
produced in
the data
Data
Wrangling
and cluster
algorithm is
used to
improve the
accuracy in
the data.
Khairulliza Ahmad
Salleh
Analysis is based on big
data
This analysis is
mainly used
for solving
problems in
data security
To identify
the
appropriate
conceptual
framework of
data analysis
Data analysis
is the solution
of improving
the security
and privacy of
data.
(N.Kshetri) The use of Big Data in
agriculture and farming
activities in developing
Countries for the purpose
of assessing the abilities
required during various
stages to value from Big
Data.
The call detail
record (CDR)
and other
information
provides
insights.
For
providing an
improved
understandin
g of the
openings and
trials of
using Big
Data for
addressing
the key
issues that
faces the
developing
world.
By
consumption
of Big Data in
big
Corporations
and also in
other
activities in
manufacturing
countries.
(H. Daki, A. El
Hannani, A. Aqqal,
A. Haidine and A.
Dahbi)
Steps to implement Big
Data solution in the smart
grid background.
Operational
data, Non-
operational
data, Meter
usage
A deluge of
data that the
energy
companies
will have to
For data
management
for smart
grids, values
are added to
17
time.
Victor M. Parra
Big data Analytical
tools.
Sustainabilit
y and
development
of the
company is
reduced.
Pentaho and
Java J2EE
application is
used in the BI
to improve the
company.
Chiranjivi Bashyal Big data
.
Algorithms are
used for
solving the
problems.
Less
accuracy are
produced in
the data
Data
Wrangling
and cluster
algorithm is
used to
improve the
accuracy in
the data.
Khairulliza Ahmad
Salleh
Analysis is based on big
data
This analysis is
mainly used
for solving
problems in
data security
To identify
the
appropriate
conceptual
framework of
data analysis
Data analysis
is the solution
of improving
the security
and privacy of
data.
(N.Kshetri) The use of Big Data in
agriculture and farming
activities in developing
Countries for the purpose
of assessing the abilities
required during various
stages to value from Big
Data.
The call detail
record (CDR)
and other
information
provides
insights.
For
providing an
improved
understandin
g of the
openings and
trials of
using Big
Data for
addressing
the key
issues that
faces the
developing
world.
By
consumption
of Big Data in
big
Corporations
and also in
other
activities in
manufacturing
countries.
(H. Daki, A. El
Hannani, A. Aqqal,
A. Haidine and A.
Dahbi)
Steps to implement Big
Data solution in the smart
grid background.
Operational
data, Non-
operational
data, Meter
usage
A deluge of
data that the
energy
companies
will have to
For data
management
for smart
grids, values
are added to
17
data ,Event
message data
and Metadata
face by the
smart grid
Big Data
equipment
and the
technical
requirements
are discussed
(Jain, P.,
Gyanchandani, M.
And Khare, N.)
Privacy and security is
considered in big data
Big data tools
to increase the
Intel’s
convenience
used for
internal web
portal
Security and
privacy
which in
terms of big
data
identity on the
basis of
anonymizatio
n techniques
encounters the
issues to
examine data
usage when
protecting the
user identity
(Tsai, C., Lai, C.,
Chao, H. And
Vasilakos, A. V.)
mining algorithm is
considered to find useful
things from the big data
preprocessing
operator is
significant in
deals with data
input aims at
cleaning,
detecting and
filtering the
unwanted,
incomplete
data to useful
one
Open issues,
security,
privacy, fault
tolerance,
data quality,
storage,
Reducing
data
complexity
for big data
clustering.
Traditional
reduction
solution is
used by
dimension
and sampling
methods
(Diksha, M.) Data driven analysis tools
are considered
Processing
data is major to
enhance with
the growth of
data. Variety,
Veracity,
Volume and
velocity in
small grids
maintained
within a
hardware
resources
Performance
evaluation,
battery
capacity,
driving range
With the
technologies
of big data,
most of the
problems able
to be handled
(Sivarajah, U.,
Kamal, M. M.,
Irani, Z. And
Weerakkody, V.)
Usage of BDA tools are
considered
40n zettabytes
data are
imitated,
generated and
consumed
Privacy
issues,
data
processing
cost are the
The technical
solutions are
implemented
18
message data
and Metadata
face by the
smart grid
Big Data
equipment
and the
technical
requirements
are discussed
(Jain, P.,
Gyanchandani, M.
And Khare, N.)
Privacy and security is
considered in big data
Big data tools
to increase the
Intel’s
convenience
used for
internal web
portal
Security and
privacy
which in
terms of big
data
identity on the
basis of
anonymizatio
n techniques
encounters the
issues to
examine data
usage when
protecting the
user identity
(Tsai, C., Lai, C.,
Chao, H. And
Vasilakos, A. V.)
mining algorithm is
considered to find useful
things from the big data
preprocessing
operator is
significant in
deals with data
input aims at
cleaning,
detecting and
filtering the
unwanted,
incomplete
data to useful
one
Open issues,
security,
privacy, fault
tolerance,
data quality,
storage,
Reducing
data
complexity
for big data
clustering.
Traditional
reduction
solution is
used by
dimension
and sampling
methods
(Diksha, M.) Data driven analysis tools
are considered
Processing
data is major to
enhance with
the growth of
data. Variety,
Veracity,
Volume and
velocity in
small grids
maintained
within a
hardware
resources
Performance
evaluation,
battery
capacity,
driving range
With the
technologies
of big data,
most of the
problems able
to be handled
(Sivarajah, U.,
Kamal, M. M.,
Irani, Z. And
Weerakkody, V.)
Usage of BDA tools are
considered
40n zettabytes
data are
imitated,
generated and
consumed
Privacy
issues,
data
processing
cost are the
The technical
solutions are
implemented
18
sensitive
issues
(Farooq.m,Waseem
.m,Mazhar.s,Kha
Iri.A,Kamal.T)
Internet of things (IOT)
provides the great future
for internet where the type
of communication
takesplace.
Wireless
sensor network
and RFID
embedded
devices are
used for
transferring
information
Security and
privacy
challenges
MEMS
combined
with nano
technology is
used for
improving the
communicatio
n system.
Hervais Simo) computational statistics
and recent advances in the
collection of data with
enhance in processing
power of computer with
plugging storage cost are
the technologies are
considered to analyze data
Customer
analytics, big
data and
healthcare, big
data for
business
optimization,
big data
science, big
data security
are focused
privacy,
security,
ethical
problems
SIEM
solutions like
IBM security
intelligence
needs to
examine
terabytes
network
events,
application
performance
and packet
captures.
Zhigao Zheng The technology of cloud
computing for large scale
RTDP has been
considered.
RTDP
architecture on
the basis of
cloud
computing
technology.
We utilize
CEP, DSMS,
batch based
map reduce,
GPU, ASIC
and CPU
technologies to
process the
data at terminal
of collection of
data.
Data privacy
issues,
complex
event
processing
issues, CEP
issues, RTDP
Qos issues,
Technology
solution
involves
communicatio
n network,
smart meters,
metering
database
management,
customer
service and
customer
premises
network
Joonsang Baek Analysis is done on
security and performance
of big data.
An identity-
based
signcryption
(IBS) security
scheme is done
Critical
security
issues of the
framework.
Performing
concurrently
the functions
of encryption
and digital
signature,
19
issues
(Farooq.m,Waseem
.m,Mazhar.s,Kha
Iri.A,Kamal.T)
Internet of things (IOT)
provides the great future
for internet where the type
of communication
takesplace.
Wireless
sensor network
and RFID
embedded
devices are
used for
transferring
information
Security and
privacy
challenges
MEMS
combined
with nano
technology is
used for
improving the
communicatio
n system.
Hervais Simo) computational statistics
and recent advances in the
collection of data with
enhance in processing
power of computer with
plugging storage cost are
the technologies are
considered to analyze data
Customer
analytics, big
data and
healthcare, big
data for
business
optimization,
big data
science, big
data security
are focused
privacy,
security,
ethical
problems
SIEM
solutions like
IBM security
intelligence
needs to
examine
terabytes
network
events,
application
performance
and packet
captures.
Zhigao Zheng The technology of cloud
computing for large scale
RTDP has been
considered.
RTDP
architecture on
the basis of
cloud
computing
technology.
We utilize
CEP, DSMS,
batch based
map reduce,
GPU, ASIC
and CPU
technologies to
process the
data at terminal
of collection of
data.
Data privacy
issues,
complex
event
processing
issues, CEP
issues, RTDP
Qos issues,
Technology
solution
involves
communicatio
n network,
smart meters,
metering
database
management,
customer
service and
customer
premises
network
Joonsang Baek Analysis is done on
security and performance
of big data.
An identity-
based
signcryption
(IBS) security
scheme is done
Critical
security
issues of the
framework.
Performing
concurrently
the functions
of encryption
and digital
signature,
19
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scalability,
flexibility,
security is
achieved
H. Khurana Smart meter The
information
about the
electricity
usage is not
perfect.
Maintenance
is difficult.
Homomorphic
encryption is
used for
protecting the
information of
electricity.
Kin Cheong Sou Smart grid cyber security
for electricity
The SCADA
and RTU is for
control.
reduction of
Cardinality
based on the
RIP and
coherence
Rajani Sharma Cloud computing Information
about data
storing and
transmission in
the internet
Security
issues arrived
Provide
security for
accessing the
data stored in
the cloud
computing
Bradley Schmerl Cloud computing is
considered to provide
fault-tolerant, scalable and
reliable environment to
big data distributed
system of management
The global data
technology can
process and
store varied
and big
volumes of
data produce
science and
enterprise
having deep
insights with
clients.
Big data
issues, the
ways to
upload data
easily on the
cloud,
disaster
recovery,
exaflop
computing
High
performance
computers is
the promising
solution
Bianchi, S. Environments and
approaches to carry out
cloud analytics for the
application of big data is
considered
It considers the
analytic areas
and big data
such as
supporting
architecture
and data
management,
scoring and
model
Few
technical
problems
must
addressed
like tuning of
models, data
quality,
privacy, data
currency and
Analytic
solution are
significant
able to
supports
organization
gain insights
from private
and public
data which is
20
flexibility,
security is
achieved
H. Khurana Smart meter The
information
about the
electricity
usage is not
perfect.
Maintenance
is difficult.
Homomorphic
encryption is
used for
protecting the
information of
electricity.
Kin Cheong Sou Smart grid cyber security
for electricity
The SCADA
and RTU is for
control.
reduction of
Cardinality
based on the
RIP and
coherence
Rajani Sharma Cloud computing Information
about data
storing and
transmission in
the internet
Security
issues arrived
Provide
security for
accessing the
data stored in
the cloud
computing
Bradley Schmerl Cloud computing is
considered to provide
fault-tolerant, scalable and
reliable environment to
big data distributed
system of management
The global data
technology can
process and
store varied
and big
volumes of
data produce
science and
enterprise
having deep
insights with
clients.
Big data
issues, the
ways to
upload data
easily on the
cloud,
disaster
recovery,
exaflop
computing
High
performance
computers is
the promising
solution
Bianchi, S. Environments and
approaches to carry out
cloud analytics for the
application of big data is
considered
It considers the
analytic areas
and big data
such as
supporting
architecture
and data
management,
scoring and
model
Few
technical
problems
must
addressed
like tuning of
models, data
quality,
privacy, data
currency and
Analytic
solution are
significant
able to
supports
organization
gain insights
from private
and public
data which is
20
development,
business
models and
user interaction
and
visualization
data
management
available on
web
3. Results
The investigation results is mainly based on graphical representation of big data analysis.
The analysis of cloud computing has been discussed. This cloud computing provides more data
security. The security attacks like virus, privacy issues and Trojan horse were analyzed.
The results of this research analysis is shown in below table.
Security level is increased by using cloud computing analysis.
Data recovery software is analyzed
Clustering algorithms is used for improving the data security.
The techniques and tools of data mining is discussed in research analysis.
21
Security
Attack
Data Security
and Privacy
Data Storage
Cloud
ComputingVirus
business
models and
user interaction
and
visualization
data
management
available on
web
3. Results
The investigation results is mainly based on graphical representation of big data analysis.
The analysis of cloud computing has been discussed. This cloud computing provides more data
security. The security attacks like virus, privacy issues and Trojan horse were analyzed.
The results of this research analysis is shown in below table.
Security level is increased by using cloud computing analysis.
Data recovery software is analyzed
Clustering algorithms is used for improving the data security.
The techniques and tools of data mining is discussed in research analysis.
21
Security
Attack
Data Security
and Privacy
Data Storage
Cloud
ComputingVirus
Fig: Cloud Computing Representation
4. Discussion section
Data security has become a highest problem in corporate networks. Predominantly it
becomes the serious problem in cloud computing environment. Data stored in a file system is easily
gets damaged by the viruses and some hackers. Then the stored data gets lost in many computer
organization networks. Occasionally the mobile phones data also gets scratched by the viruses. So
these are the limitations in data security of big data analysis.
The importance of this analysis is to achieve the privacy protection and data security
problems in cloud computing architecture. The cloud computing is mainly needed for the solution
of many problems in different information technologies.
The most important result of this analysis is the cloud computing technology extremely
retrieves the efficient data for more data security. The big data analysis study are mainly used to
identify the factors for future research. The cloud computing is mainly used for information
handling, investigation processes. And it also provides huge development of storage data. In this
report the security of data is improved by using cloud computing analysis.
22
4. Discussion section
Data security has become a highest problem in corporate networks. Predominantly it
becomes the serious problem in cloud computing environment. Data stored in a file system is easily
gets damaged by the viruses and some hackers. Then the stored data gets lost in many computer
organization networks. Occasionally the mobile phones data also gets scratched by the viruses. So
these are the limitations in data security of big data analysis.
The importance of this analysis is to achieve the privacy protection and data security
problems in cloud computing architecture. The cloud computing is mainly needed for the solution
of many problems in different information technologies.
The most important result of this analysis is the cloud computing technology extremely
retrieves the efficient data for more data security. The big data analysis study are mainly used to
identify the factors for future research. The cloud computing is mainly used for information
handling, investigation processes. And it also provides huge development of storage data. In this
report the security of data is improved by using cloud computing analysis.
22
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5. Conclusion
The data security has been implemented by using graphical representation of cloud
computing algorithm. The hacked data is recovered by using the software recovery has been
investigated. The data processing in big data analysis were discussed by using mixed cloud
computing method. The different types of security attacks like viruses, Trojan horse attacks are
analyzed clearly in the tabulation of material and method section. Based on the security attacks the
comprehensive explanation of the steps of the attacks are also analyzed. The accuracy of data and
prevention of data hacking is done by using the clustering algorithm. cyber security analysis,
collection of data in big data analysis, performance evaluation,availability,scalability,pattern
analysis, data processing analysis, security challenges are in materials and method.
References
[1]D. Pham, A. Syed, A. Mohammad and M. Halgamuge, "Threat Analysis of Portable Hack
Tools from USB Storage Devices and Protection Solutions", 2017.
[2]D. Pham, M. Halgamuge, A. Syed and P. Mendis, "Optimizing Windows Security Features to
Block Malware and Hack Tools on USB Storage Devices", 2017.
[3]D. Pham, A. Syed and M. Halgamuge, "Universal serial bus based software attacks and
protection solutions", 2017.
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Classification Algorithms using Data Mining: Crime and Accidents in Denver City the
USA", 2017.
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Business Intelligence Open Source Tools Processing Big Data to Evaluate
Performances", International Journal of Advanced Computer Science and Applications, vol.
7, no. 10, 2016.
23
The data security has been implemented by using graphical representation of cloud
computing algorithm. The hacked data is recovered by using the software recovery has been
investigated. The data processing in big data analysis were discussed by using mixed cloud
computing method. The different types of security attacks like viruses, Trojan horse attacks are
analyzed clearly in the tabulation of material and method section. Based on the security attacks the
comprehensive explanation of the steps of the attacks are also analyzed. The accuracy of data and
prevention of data hacking is done by using the clustering algorithm. cyber security analysis,
collection of data in big data analysis, performance evaluation,availability,scalability,pattern
analysis, data processing analysis, security challenges are in materials and method.
References
[1]D. Pham, A. Syed, A. Mohammad and M. Halgamuge, "Threat Analysis of Portable Hack
Tools from USB Storage Devices and Protection Solutions", 2017.
[2]D. Pham, M. Halgamuge, A. Syed and P. Mendis, "Optimizing Windows Security Features to
Block Malware and Hack Tools on USB Storage Devices", 2017.
[3]D. Pham, A. Syed and M. Halgamuge, "Universal serial bus based software attacks and
protection solutions", 2017.
[4]A. Gupta, A. Syed, A. Mohammad and M. Halgamuge, "A Comparative Study of
Classification Algorithms using Data Mining: Crime and Accidents in Denver City the
USA", 2017.
[5]V. M., A. Syed, A. Mohammad and M. N., "Pentaho and Jaspersoft: A Comparative Study of
Business Intelligence Open Source Tools Processing Big Data to Evaluate
Performances", International Journal of Advanced Computer Science and Applications, vol.
7, no. 10, 2016.
23
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Areas and Algorithms used in Data Wrangling in Big Data", Charles Sturt University.
[7]H. Khan, A. Syed, A. Mohammad and M. Halgamuge, "Computer Virus and Protection
Methods Using Lab Analysis", Charles Sturt University.
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Threats in Cloud Computing Associated with Big Data", 2017.
[9]S. Kalid, A. Syed, A. Mohammad and M. Halgamuge, "Big-Data NoSQL Databases: A
Comparison and Analysis of "Big-Table", "DynamoDB", and "Cassandra"", 2017.
[10]B. Ekanayake, M. Halgamuge and A. Mohammad, "Review: Security and Privacy Issues of
Fog Computing", 2017.
[11]S. Munugala, A. Syed, G. Brar, A. Mohammad and M. Halgamuge, "The Much Needed
Security and Data Reforms of Cloud Computing in Medical Data Storage", 2017.
[12]T. Hewage, M. Halgamuge, A. Syed, A. Mohammad and C. Bellamy, "Review: Big Data
Techniques of Google, Amazon and Social Networks from 2007-2015", 2017.
[13]M. Singh, M. Talalaeva, M. N. Halgamuge, A. Syed and G. Ekici, "A Review on Security
and Privacy Challenges of Big Data", 2017.
[14]R. Jeewantha, M. N. Halgamuge, G. Ekici, A. Mohammad and A. Syed, "Classification
Performance Analysis in Medical Science: Using Kidney Disease Data", 2017.
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during 1985–2016 in Australia and India", International Journal of Disaster Risk Reduction,
vol. 24, pp. 1-11, 2017.
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review", 2017. .
[18]C. Tsai, C. Lai, H. Chao and A. Vasilakos, "Big data analytics: a survey", 2017. .
24
Areas and Algorithms used in Data Wrangling in Big Data", Charles Sturt University.
[7]H. Khan, A. Syed, A. Mohammad and M. Halgamuge, "Computer Virus and Protection
Methods Using Lab Analysis", Charles Sturt University.
[8]K. Kaur, A. Syed, A. Mohammad and M. Halgamuge, "Review: An Evaluation of Major
Threats in Cloud Computing Associated with Big Data", 2017.
[9]S. Kalid, A. Syed, A. Mohammad and M. Halgamuge, "Big-Data NoSQL Databases: A
Comparison and Analysis of "Big-Table", "DynamoDB", and "Cassandra"", 2017.
[10]B. Ekanayake, M. Halgamuge and A. Mohammad, "Review: Security and Privacy Issues of
Fog Computing", 2017.
[11]S. Munugala, A. Syed, G. Brar, A. Mohammad and M. Halgamuge, "The Much Needed
Security and Data Reforms of Cloud Computing in Medical Data Storage", 2017.
[12]T. Hewage, M. Halgamuge, A. Syed, A. Mohammad and C. Bellamy, "Review: Big Data
Techniques of Google, Amazon and Social Networks from 2007-2015", 2017.
[13]M. Singh, M. Talalaeva, M. N. Halgamuge, A. Syed and G. Ekici, "A Review on Security
and Privacy Challenges of Big Data", 2017.
[14]R. Jeewantha, M. N. Halgamuge, G. Ekici, A. Mohammad and A. Syed, "Classification
Performance Analysis in Medical Science: Using Kidney Disease Data", 2017.
[15] M. Halgamuge, "Review: Weak radiofrequency radiation exposure from mobile phone
radiation on plants", Electromagnetic Biology and Medicine, vol. 36, no. 2, pp. 213-235,
2016.
[16]M. Halgamuge and A. Nirmalathas, "Analysis of large flood events: Based on flood data
during 1985–2016 in Australia and India", International Journal of Disaster Risk Reduction,
vol. 24, pp. 1-11, 2017.
[17]P. Jain, M. Gyanchandani and N. Khare, "Big data privacy: a technological perspective and
review", 2017. .
[18]C. Tsai, C. Lai, H. Chao and A. Vasilakos, "Big data analytics: a survey", 2017. .
24
[19] H. Simo, "Big Data: Opportunities and Privacy Challenges", 2017.
[20]U. Sivarajah, M. Kamal, Z. Irani and V. Weerakkody, "Critical analysis of Big Data
challenges and analytical methods", 2017. .
[21] M. Farooq, M. Waseem, S. Mazhar, A. Khairi and T. Kamal, "A Review on Internet of
Things (IoT)", 2017.
[22]N. Kshetri, "The emerging role of Big Data in key development issues: Opportunities,
challenges, and concerns", Big Data & Society, vol. 1, no. 2, p. 205395171456422, 2014.
[23]H. Daki, A. El Hannani, A. Aqqal, A. Haidine and A. Dahbi, "Big Data management in
smart grid: concepts, requirements and implementation", Journal of Big Data, vol. 4, no. 1,
2017.
[24] Khairulliza Ahmad Salleh, "The big data security challenge", Network Security, vol. 2015,
no. 1, pp. 12-14, 2015.
[25]J. Baek, Q. Hieu Vu and J. K. Liu, "A secure cloud computing based framework for big data
information management of smart grid", 2017.
[26]K. Sou, H. Sandberg and K. Johansson, "On the Exact Solution to a Smart Grid Cyber-
Security Analysis Problem", IEEE Transactions on Smart Grid, vol. 4, no. 2, pp. 856-865,
2013.
[27]R. Sharma, and R. Trivedi, "Literature review: Cloud Computing –Security Issues, Solution
and Technologies", International Journal of Engineering Research, vol. 3, no. 4, pp. 221-
225, 2014.
[28]H. Khurana, M. Hadley, Ning Lu and D. Frincke, "Smart-grid security issues", IEEE
Security & Privacy Magazine, vol. 8, no. 1, pp. 81-85, 2010.
[29] Z. Zheng, P. Wang, J. Liu and S. Sun, "Real-Time Big Data Processing Framework:
Challenges and Solutions", 2017.
[30]M. Assuncao, R. Calheiros and S. Bianchi, "Big Data computing and clouds: Trends and
future directions", 2017.
[31]P. Neves and B. Schmerl, "Big Data in Cloud Computing: features and issues", 2017.
[32] D. M and R. T. S, "A Survey on Big Data Energy Based on Smart Grid", 2017.
25
[20]U. Sivarajah, M. Kamal, Z. Irani and V. Weerakkody, "Critical analysis of Big Data
challenges and analytical methods", 2017. .
[21] M. Farooq, M. Waseem, S. Mazhar, A. Khairi and T. Kamal, "A Review on Internet of
Things (IoT)", 2017.
[22]N. Kshetri, "The emerging role of Big Data in key development issues: Opportunities,
challenges, and concerns", Big Data & Society, vol. 1, no. 2, p. 205395171456422, 2014.
[23]H. Daki, A. El Hannani, A. Aqqal, A. Haidine and A. Dahbi, "Big Data management in
smart grid: concepts, requirements and implementation", Journal of Big Data, vol. 4, no. 1,
2017.
[24] Khairulliza Ahmad Salleh, "The big data security challenge", Network Security, vol. 2015,
no. 1, pp. 12-14, 2015.
[25]J. Baek, Q. Hieu Vu and J. K. Liu, "A secure cloud computing based framework for big data
information management of smart grid", 2017.
[26]K. Sou, H. Sandberg and K. Johansson, "On the Exact Solution to a Smart Grid Cyber-
Security Analysis Problem", IEEE Transactions on Smart Grid, vol. 4, no. 2, pp. 856-865,
2013.
[27]R. Sharma, and R. Trivedi, "Literature review: Cloud Computing –Security Issues, Solution
and Technologies", International Journal of Engineering Research, vol. 3, no. 4, pp. 221-
225, 2014.
[28]H. Khurana, M. Hadley, Ning Lu and D. Frincke, "Smart-grid security issues", IEEE
Security & Privacy Magazine, vol. 8, no. 1, pp. 81-85, 2010.
[29] Z. Zheng, P. Wang, J. Liu and S. Sun, "Real-Time Big Data Processing Framework:
Challenges and Solutions", 2017.
[30]M. Assuncao, R. Calheiros and S. Bianchi, "Big Data computing and clouds: Trends and
future directions", 2017.
[31]P. Neves and B. Schmerl, "Big Data in Cloud Computing: features and issues", 2017.
[32] D. M and R. T. S, "A Survey on Big Data Energy Based on Smart Grid", 2017.
25
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