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Conference papers
A Behavior-Based Approach for Malware Detection
Abstract : Malware is the fastest growing threat to information technology systems. Although a single absolute solution for defeating malware is improbable, a stacked arsenal against malicious software enhances the ability to maintain security and privacy. This research attempts to reinforce the anti-malware arsenal by studying a behavioral activity common to software – the use of handles. The characteristics of handle usage by benign and malicious software are extracted and exploited in an effort to distinguish between the two classes. An automated malware detection mechanism is presented that utilizes memory forensics, information retrieval and machine learning techniques. Experimentation with a malware dataset yields a malware detection rate of 91.4% with precision and recall of 89.8% and 91.1%, respectively.
Cited literature [28 references]
https://hal.inria.fr/hal-01716397
Contributor : Hal Ifip <>
Submitted on : Friday, February 23, 2018 - 3:50:07 PM
Last modification on : Friday, February 23, 2018 - 3:52:06 PM
Long-term archiving on: : Friday, May 25, 2018 - 7:17:07 AM
Contributor : Hal Ifip <>
Submitted on : Friday, February 23, 2018 - 3:50:07 PM
Last modification on : Friday, February 23, 2018 - 3:52:06 PM
Long-term archiving on: : Friday, May 25, 2018 - 7:17:07 AM
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456364_1_En_11_Chapter.pdf
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Distributed under a Creative Commons Attribution 4.0 International License