Edward Wu is a Principal Data Scientist at ExtraHop Networks, leading AI/ML and Detection capabilities. 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 the MITRE ATT&CK framework. Prior to Extrahop, he worked in automated binary analysis and software defenses at UW Seattle and UC Berkeley.
Hype and Reality: Practical advices for implementing and evaluating AI/ML for Cybersecurity
For a long time, AI/ML has been portrayed as the magic “silver bullet” that would solve everything in cybersecurity. However, as evident in the last few years, the promises of AI/ML haven’t materialized. Cyber defenders and practitioners today are still faced with increasingly sophisticated attackers, rapidly growing complexity of modern cyber infrastructures, and persistent talent shortage. In this talk, I will separate the hype from the reality, present real-world examples of where 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. No prior data science knowledge is required.
When: Monday, February 8, 2021 @ 11:30 a.m.
Where: Zoom Online Meeting