Big Data Analysis | ENISA

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Added on 2020-02-24

Big Data Analysis | ENISA

Added on 2020-02-24

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Running Head: IT RISK MANAGEMENTIT RISK MANAGEMENTName of the StudentName of the University

1IT RISK MANAGEMENTTable of ContentsENISA Big Data Threat Landscape 2016......................................................................2Question 1......................................................................................................................2Question 2......................................................................................................................4Question 3......................................................................................................................6Question 4......................................................................................................................8Question 5......................................................................................................................8References....................................................................................................................11

2IT RISK MANAGEMENTENISA Big Data Threat Landscape 2016Question 1Provide a brief overview of the case study and prepare a diagram for the ENISA Big Datasecurity infrastructure.There is an elaboration of threats which is related to the Big Data in the case study.There have been much gained traction within last few years and thus the data storage andinformation technology has been anticipated to play a serious role on several new aspects inthe society (Marinos, 2013). The potential impact of the Big Data has been acknowledged bythe European Commission by identifying the strategic approach in the Big Data. The aspectsthat can be developed and affected by the development of information technology and bigdata are food security, health security, climate and resources that are efficient to energy,intelligent transport system and smart cities. The data is thus conceivable to the economicdrive in the organizational system. In the field of science and research there is also a largeimpact of the Big Data that continues to escalate. Thus, many agencies and institution all overthe globe are planning to launch the Big Data projects for better exploitation of data analysisand cloud computing. Technologies of Big Data can also be used in the application ofmilitary field, such as combat accommodating or fighting virtual or real terrorism. Thusidentifying and collecting the information from heterogeneous sources from any real filed oropen sources has a great impact (Marinos, Belmonte &Rekleitis, 2014). High tech and highlynovel ICT systems are used in the approach of Big Data. But increase in the use of this BigData technology has also frequently increased the chances of cyber attacks, data breaches andhacking. The increases of this kind of challenges are both trending the number insophisticated and impact. By increase in the number of usability of business in Big Data and

3IT RISK MANAGEMENTorganizations, the attackers get incentives for developing and specializes attacks against BigData analysis. This technology are used by tools that has also the capability that combats thecyber threats that offers privacy and security professionals that has valuable insights inincident management and threats. In the area of Big Data analysis ENISA delivers the area ofthis Threats Landscapes by the inputs from the ENISA Threat Landscape activities. The casestudy discusses about the architecture, ENISA threat taxonomy the targeted audience of BigData approach, the asset taxonomy of Big Data, the methodology by which the case study hasbeen carried out, gaps of the study and finally recommending the approach. The infrastructure layer in ENISA by Big Data is depicted by the Cloud Computing.IT helps in meeting the infrastructure requirement like the elasticity, cost-effectiveness andthe ability to scale up and down. The security infrastructure of Big Data system in ENISAfollows:Data sources layer: The layer consist of streaming data from the data sourcedisparate, sensor and structured information like relational database, semi-structured and unstructured data.Integration process layer: The layer only concern with important data havingpre-processing operation acquiring data hence integrated the datasets into astructured form. Data storage layer: This data layer is consist of large variety of resources likeRDF stores, NoSQL, distributed file system and NewSQL database, that aresuitable for large number of datasets that persistent storage.Analytics and computing model layer: The layer encapsulates different datatools like the MapReduce that runs over the resources that are stored, havingthe model programming and data management.

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