1st Edition

Big Data Analytics with Applications in Insider Threat Detection

    ISBN 9780367657420
    578 Pages
    Published September 30, 2020 by Auerbach Publications

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    Sale Price USD $54.95
    USD $54.95
    ISBN 9781498705479
    578 Pages 50 B/W Illustrations
    Published December 1, 2017 by Auerbach Publications

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    Sale Price USD $129.95
    USD $129.95
    ISBN 9781315119458
    578 Pages 50 B/W Illustrations
    Published November 22, 2017 by Auerbach Publications

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    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.

    Supporting Technologies. Introduction. Data Mining Techniques. Cyber Security and Malware. Data Mining for Malware Detection. Conclusion. Stream-Based Novel Class Detection. Stream Mining. Novel Class Detection Problem. SNOD. Conclusion. Reactively Adaptive Malware. Reactively Adaptive Malware. RAMAL Design. RAMAL Implementation. SNODMAL. Introduction. SNODMAL Design. SNODMAL Implementation. SNODMAL FOR RAMAL. SNODMAL Extensions. Introduction. SNODMAL on the Cloud. SNODCAL. SNODMAL++. Conclusion. Summary and Directions. References. Appendix A: Data Management Systems. Appendix B: Malware Products.


    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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