Big data and Cybercrimes Prevention and Risks
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1 Big data and Cybercrimes Prevention and Risks P. Thenmozhi Dr.Neelamalar Maraimalai Department of Media Sciences, College of Engineering Guindy, Anna University, Chennai, Tamil Nadu, India
2 INTRODUCTION 24 /7 online lifestyle gives enormous opportunities to reach anyone from anywhere but at the same time such activity gives chances to cyber criminals. Big data is associated with crime and it has huge power and influence to solve the security problem and in creating cyber risks as well.
3 The study analyses the way how big data helps to fight against cyber crimes toward predicting and in preventing them. The study also analyses the risk perspectives associated with big data.
4 Big Data Big data can be explained in many ways based on its application of ideas and field Lessig (1999) defined the Big data on technological cases, he states that Big Data is odd to four forces they are market, law, social norms and architecture of social systems and also have an impact in all fields. Boyd & Crawford (2009) define Big Data as a cultural, technological, and scholarly phenomenon that rests on the interplay of technology, analysis and mythology.
5 Big Data can be defined in several ways, based on its application of ideas in the field and usage. Manovich (2012) explains that the Big Data is less about data and bigger than about a capacity to search, aggregate, and do a cross-reference of large data sets. The three classes of people in the realm of Big Data are those who create data, collect data and expertise to analyze the data. Manovich(2012)
6 Big Data and Cyber crime O Berien (2013) stated that More data production without security and awareness will definitely lead to organized crime. Goodman(2015) explains that when we leak data, it s not just captured by corporation (or) Government but also by criminals.
7 Goodman s law stated that the more data you produce and store, the more organized crime is happy to consume. For example, in Mumbai attack 2008, Lasshkare-taiba cleverly utilized cyber space for targeting venues and they simply processed the big data for their plan.
8 Durbin (2012) discussed the top five global security threats identified by the ISF (Information Security Forum) for The Unintended Consequences of State Intervention Big Data Mobile Applications Internet of Things (IoT) Cybercrimes.
9 Apart from these, the growing skills gap in the information security industry has exposed the sector to a larger range of security threats.
10 Big data and cyber security Big data is acting like a additional tool to predict and detect the crime. The huge electronic communication data can be analysed with the help of Big data technologies. The Data Security Council of India stated that the key challenge of cyber space is proper cyber security and it can be achieved by Big data management.
11 Wong (2016) states that hackers are getting better and businesses are increasingly at risk. To prevent and detect the highly vulnerable crimes the organizations are developing the Big data analytics as a solution. Big data analytics are already being used for fraud prevention, cyber security detection, social analysis and real-time multimodal surveillance. Security solutions are emerging for the big data, but security teams with internal knowledge is lacking and the data scientists who specialize in cyber security and big data are few with high demand.
12 PwC (PricewaterhouseCoopers)(2014), reported that Corporate cyber crime is increasing, the number of security incidents climbed to 38% in 2015 and is growing high, and the prevention and detection methods have proved largely ineffective.
13 According to Internet security report (2014) there are five important ways to improve cyber security in an organization which are: Combat persistence threats Mitigate exposure to cyber attacks Mitigate fraud on business process Privation activism on Network Identify inside threats.
14 Big data and technologies Big data analytics
15 Big data and technologies Big data analytics can be used to process and analyze the structured and unstructured data automatically to identify patterns or correlations The companies like IBM, Oracle, SAS, Microsoft, SAP. EMC, HP and DELL are aggressively trying to maximize their profits from the big data phenomenon by introducing the insight to protect from cyber crime and offering the Big data security solutions through Big data analytics.
16 Big data Legal and regulatory issues The law-making process is slow compared to technology's speed of change. This lag often means that new technical solutions remain unregulated or are constrained by outdated legislation. organizations must ensure that their use of big data analytics complies with existing legislation and regulations, while keeping an eye on the future.
17 Big data and Social Media risks Organized criminals are using knowledge management business to go behind the Big data in an efficient way through social media.(goodman, 2015) 40% of social media users are exposed to Facebook malware. Facebook koobface
18 Big data and identity theft are a great fodder in the cyber world. Identity theft through social media data is a growing field where children are the fastest growing victim groups. On the other side Hate crimes and Burglar 2.0 crimes are increasing and they are digging the data from social media in a effective manner and within a fraction of seconds.(goodman, 2015)
19 CONCLUSION Big Data promises to open new horizons in all aspects of business and analytics, but there is an obvious downside too. In the ocean of Big data there are numerous risks and Big data analytics stick together to help in security activity, in either way providing the information to the criminal in a fraction of seconds.
Executive Director Centre for Cyber Victim Counselling www.drjaishankar.co.nr / www.cybervictims.org
Dr. K. Jaishankar Senior Assistant Professor Department of Criminology and Criminal Justice Manonmaniam Sundaranar University Tirunelveli, Tamil Nadu, India Executive Director Centre for Cyber Victim Counselling
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