Big Data Analytics for Cyber Security
Pelin Angın, Bharat Bhargava, Rohit Ranchal · Security and Communication Networks · 2019
e era of Internet of ings with billions of connected devices has created an ever larger surface for cyber attackers to exploit, which has resulted in the need for fast and accurate detection of those attacks.e developments in mobile computing, communications, and mass storage architectures in the past decade have brought about the phenomenon of big data, which involves unprecedented amounts of valuable data generated in various forms at a high speed.e ability to process these massive amounts of data in real time using big data analytics tools brings along many bene ts that could be utilized in cyber threat analysis systems.By making use of big data collected from networks, computers, sensors, and cloud systems, cyber threat analysts and intrusion detection/prevention systems can discover useful information in real time.is information can help detect system vulnerabilities and attacks that are becoming prevalent and develop security solutions accordingly.Big data analytics will be a must-have component of any e ective cyber security solution due to the need of fast processing of the high-velocity, high-volume data from various sources to discover anomalies and/or attack patterns as fast as possible to limit the vulnerability of the systems and increase their resilience.Even though many big data analytics tools have been developed in the past few years, their usage in the eld of cyber security warrants new approaches considering many aspects including (a) uni ed data representation, (b) zero-day attack detection, (c) data sharing across threat detection systems, (d) real time analysis, (e) sampling and dimensionality reduction, (f ) resource-constrained data processing, and (g) time series analysis for anomaly detection.is special issue has attracted original contributions that utilize and build big data analytics solutions for cyber