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The Use of Machine Learning in Offensive Cybersecurity Applications
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The Use of Machine Learning in Offensive Cybersecurity Applications

Fri, April 30 at 8:00 AM - 9:00 AM GMT+5:30DeepTech AppDev

Offensive cybersecurity operations are a part of nation-state conflicts. There are also situations wherein law enforcement may use offensive operations to breach criminal networks/websites. Machine learning has a role to play in these offensive operations. While most researchers focus on defensive machine learning (IDS/IPS, Antivirus, etc.), there are applications in offensive cybersecurity. Come to this talk to explore them.

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About the speaker

Chuck Easttom

Chuck Easttom

Adjunct Lecturer, Georgetown University

Dr. Chuck Easttom is the author of 31 books, including several on computer security, forensics, and cryptography. His books are used at over 60 universities. He has also authored scientific papers (over 70 so far) on digital forensics, cyber warfare, cryptography, and applied mathematics. He is an inventor with 22 computer science patents. He holds a Doctor of Science in cyber security (dissertation topic: a study of lattice-based cryptographic algorithms for post quantum computing) and a Ph.D. in Technology, focusing on nanotechnology (Dissertation title: The Effects of Complexity on Carbon Nanotube Failures). and three master's degrees (one in applied computer science, one in education, and one in systems engineering). He is a Senior Member of the IEEE and a Senior Member of the ACM as well as a member of IACR (International Association of Cryptological Research) and INCOSE (International Council on Systems Engineering). He is also a Distinguished Speaker of the ACM (Association of Computing Machinery)and a Distinguished Visitor of the IEEE Computer Society. He currently is an adjunct lecturer for Georgetown University.

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