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Big Data Security: A Case Study

   

Added on  2019-11-25

11 Pages2527 Words62 Views
Running Head: INFORMATION SECURITY 1Information Security

Information Security 2Part 1The case study has highlighted the issue related to big data security in the data storage systems. The term big data refers to different types of algorithms, technology and the infrastructure which can store and analyze massive amount of data. There are several and diversified sources of big data which are used for adoption and the development of big data applications. In the present times, big data applications are necessary to increase the efficiency and the effectiveness of the decision-making in large business organizations. In the present times, data and knowledge is considered as the most crucial asset for the business organizations. The applications of big data are ranging from the military, science and business intelligence (Lopez & Saleem, 2017). Although big data has immense applications in different work and operations in business enterprises, it also bears several types of security and privacy risk for the users. Big data applications are becoming target of various threat agents and with time, several specialized attacks will also be devised to exploit the vulnerabilities and the threats of big data. It has been identified that the big data threat includes but is not limited to the theft of ordinary data and new breaches and degradation and threats have emerged which can impact the data which is collectedwith the help of big data collection method. The frequency of outsourcing in big data can introduce new type of breach, leakage and degradation threats. They can also impact on the privacy and data protection. In big data system, additional time is required for parallelization andingestion; however, the requirement of additional time can increase the impact and frequency of data leakage and breach. In addition to it, several security challenges and issues are aligned with big data asset owners and the interest of different asset owners are not aligned together and mightbe in conflict. The security countermeasures may be in conflicts which can create a difficult big data security landscape. The report has highlighted the security issues with the big data.

Information Security 3Moreover, the report has identified the gaps between big threat and countermeasures in the big data. If the business organizations adopt basic privacy and security practices, it can decrease the privacy and security risks in big data organizations. The initial security arrangements can be beneficial for the organization and it will reduce the cost and effort required to provide ad hoc solutions later on (Sharvari, Solanki, Kumar, & Nilanjan, 2017). The current countermeasure technique should adapt the existing solutions against the traditional data threats in the big data environment. It should also focus on adaptation of the existing solutions to the big data challenges. The report has provided several recommendations such as departure from the traditional data security methods to big data specific solutions. The business organizations should also identify the gaps and needs in the current standardization activities andfocus on training and specialization of the professionals. The organization should define the toolsand techniques for the security and the privacy protection and simplify or customize the solutionsfor mitigating risk and threats in the business organizations (Mather, Kumaraswamy, & Latif, 2009).

Information Security 4Figure: Information and Security Issues Part 2With the advent of big data, several new security and privacy threats have arisen. The threats refer to any event which may provide unauthorized access, damage or denial of service toa third party organization. According to the personal perception, the information leakage due to human error or sharing is the primary threat to the business organizations. The threats refer to all those security breaches which are caused by human errors, misconfiguration or clerical errors. The human errors refer to the misconfiguration, slips or errors due to skill disadvantage or use of simple or easy to guess user names, and mistakes related to software upgrading or procedural flaws (Craig & Ludloff, 2011).

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