Today's malware mutates randomly to avoid detection, but reactively adaptive malware is more intelligent, learning and adapting to new computer defenses on the fly. Using the same algorithms that antivirus software uses to detect viruses, reactively adaptive malware deploys those algorithms to outwit antivirus defenses and to go undetected. This book provides details of the tools, the types of malware the tools will detect, implementation of the tools in a cloud computing framework and the applications for insider threat detection.

About the Author:

Dr. Bhavani Thuraisingham is the Louis A. Beecherl, Jr. Distinguished Professor of Computer Science and the Executive Director of the Cyber Security Research and Education Institute (CSI) at the University of Texas at Dallas.

Dr. Kevin W. Hamlen is an Assistant Professor in CS at UTD where he directs the Software Security Lab.

Dr. Latifur R. Khan is currently an Associate Professor in CS at UTD.

Dr. Mehedy Masud is an associate professor at the College of Information Technology, United Arab Emirates University.

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Big Data Analytics With Applications in Insider Threat Detection

Thuraisingham, Bhavani; Parveen, Pallabi; Masud, Mohammad Mehedy; Khan, Latifur

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