Big Data Cyber Security Analytics

Research topic: Big Data Cyber Security Analytics

Background:

According to Gartner a research firm, Big Data analytics will play a fundamental role as far as Cyber security is concerned. The Cyber Security analytics of Big Data would enable the organizations to sift their massive organizational data in order to maintain data security. By considering the outside and inside aspects of data security, organizations would be in position to detect patterns of cyber crimes, eliminate threats and uncover hidden relationships (Moura & Serrao, 2003). The move would enable the organizations to view the broader and big picture of cyber security landscape of the organizations. The cyber security analytics dealing with the Big Data is normally applicable in various aspects such as: network monitoring, authorization of users, authentication, identity management, risk compliance and systems of governance (Lehto, 2012). The adoption of the new technology by various organizations is likely to attract Cyber security controls in the form of data loss prevention, anti-malware and convectional firewalls.

The information needed to reveal security events loses value over time and timely data intelligent analytics is vital as the cyber criminals normally move quickly to commit the cyber attacks. Therefore, cyber security analytics must therefore blend real-time analytics on data in motion and the historical analysis of the rest of the data (Alexander & Wang, 2015). By the organizations adopting security specific analytics, they are in a better position to establish new associations to uncover cyber crimes facts and patterns. In addition, the real-time security measures might also be invaluable in detecting and dealing with the new types of threats.

Aims:

In my project, I will work on real-time cyber-attack prediction and mitigation solutions leveraging Big Data analytics, in order for organizations to detect new threats early and react quickly before they propagate.

More specifically, this project aims to:

  • Design a novel model for real-time Cyber Security analytics to detect anomalies and abnormal behaviors immediately. Huge volumes of Big Data from diverse sources need to be observed, visualized and analyzed in real-time manner to achieve automated controls and advanced predictive capabilities.
  • Establish software tools which implement the proposed model, in particular, based on open source large-scale Big Data processing platform such as Hadoop.
  •  Evaluate and demonstrate the Cyber Security analytics tool on Amazon Cloud.
  • Experiments will be conducted to benchmark the performance of the developed model.

Methodology:

The research would use both qualitative and quantitative methods to evaluate the impact of the Big Data security Analytics in dealing with the continuing and recent problems in response and detection of the cyber attacks in most of the organizations dealing with huge data. Open ended questionnaires and closed ended questionnaires shall be used to establish how the data crackers and hackers use the open source and data gaps to interfere with the organizations’ data (Lehto, 2012). The research would also use interviews to establish the security policies and mechanisms being implemented by various organizations in order to deal with the enterprise data security in the challenging tasks (Kiran, 2014). The research would also use interviews to establish how data collection, integration and machine learning approaches might be of great help in reducing and curbing expansion of cyber crimes and maintaining cyber security. The research will establish how Hadoop which is a software framework for processing and storing Big Data under the Big Data Analytics may influence the cyber security using both qualitative and quantitative methods to analyze the data.

Bibliography:

Alexander & Wang, (2015). Big Data in Distributed Analytics, Cyber security, Cyber Warfare and Digital Forensics. Digital Technologies Journal. Vol. 1(1), Pp. 22-27.

Kiran, J. (2014). Big Data Analytics with Hadoop to analyze Targeted Attacks on Enterprise Data. International Journal of Computer Science and Information Technologies, Vol. 5 (3), Pp. 3867-3870.

Lehto, M. (2012). Cyber Security: Analytics, Technology and Automation. New York Publishers.

Moura & Serrao, (2003) Security and Privacy Issues of Big Data: An Open and Secure Digital Rights Management Solution. International Conference e-Society.