Big data analytics for security intelligence
I. Sumaiya Thaseen, Aswani Kumar Cherukuri, Gang Li, Xiao Liu
Abstract
There is a tremendous increase in the frequency of cyberattacks due to the rapid growth of the Internet. These attacks can be prevented by many well-known cybersecurity solutions. However, many traditional solutions are becoming obsolete because of the impact of big data over networks. Hence, corporate research has shifted its focus on security analytics. The role of security analytics is to detect malicious and normal events in real time by assisting network managers in the investigation of real-time network streams. This technique is intended to enhance all traditional security approaches. The various challenges have to be addressed to investigate the potential of big data for information security. This chapter will focus on the major information security problems that can be solved by big data applications and outlines research directions for security intelligence by applying security analytics. This chapter presents a system called seabed, which facilitates efficient analytics on huge encrypted datasets. Besides, we will discuss a lightweight anomaly detection system (ADS) that is scalable in nature. The identified anomalies will aid us to provide better cybersecurity by examining the network behavior, identifying the attacks and protecting the critical infrastructures.