Final Report: ITC571 - Emerging Tech and Cloud Security Issues

This report addresses the critical importance of data security and privacy in cloud computing, a technology reshaping modern data management. The report explores the vulnerabilities inherent in cloud environments, including threats from viruses and hackers, and emphasizes the necessity of robust security measures. It examines the challenges faced by corporate organizations in securing their data and discusses various security measures, including antivirus software and the need for advanced security protocols. The report also reviews existing literature on the subject, including studies on USB security risks, the impact of viruses, and the application of data wrangling and clustering algorithms for data analysis and security enhancement. The research aims to analyze security attacks in corporate networks and provide solutions to improve security for advanced technologies, focusing on real-time applications and the implementation of clustering algorithms to prevent data hacking. This report is a valuable resource for understanding and addressing the key issues related to cloud data security.

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Subject ITC571 – Emerging Technology and Innovations
Assignment No Final Report
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School of Computing and Mathematics, Charles Sturt University, Melbourne, Victoria
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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
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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
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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.
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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.
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 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.
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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.
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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
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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
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(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
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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
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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.
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