2021-06-12, 13:00–13:45, Track 3
For a long time, AI/ML has been portrayed as the magic "silver bullet" that would solve everything in cybersecurity. In this talk, I will separate the hype from reality, present real-world examples of where the application of AI/ML is feasible and beneficial, and highlight challenges and limitations. At the end of the talk, I will also provide concrete advice on how to best implement and evaluate AI/ML technologies.
Edward Wu leads AI/ML and detection capabilities at ExtraHop Networks. He specializes in the intersection of machine learning, software engineering, and cybersecurity, and has built innovative next-gen technology for behavioral attack detection, automated security operation, network/application monitoring, and cloud workload security from scratch. He holds 10+ patents in ML and cybersecurity, co-authored 3 papers in top academic security conferences, and is a contributor to MITRE ATT&CK framework. Prior to Extrahop, he worked in automated binary analysis and software defenses at UW Seattle and UC Berkeley.