Title: Is Machine learning a silver bullet for all security problems?
| Date and Time of Talk: | 16-December-2021 | 14:00 -14:40 |
Abstract
Last couple of decades have seen an explosive growth in computing and communication technologies resulting in more and more people and devices connecting with each other, this shift has resulted in a large number of security incidents generated every second to the point that it has become unmanageable by humans and automated solutions are sought. Machine learning has shown tremendous promise in other areas such as speech and image processing and it is being deployed to solve security problems that range from detecting phishing to identifying malware, from anomaly detection to automating the incident response. Some of these solutions are very effective but others aren’t so much. In this talk we will cover security problems and the ML solutions used to solve those problems and identify the challenges faced by some that keep them from being optimal.
Biography
Moazzam Khan is currently working as a software engineer at IBM in the area of Threat Intelligence, his team is building a next-gen security platform for integration of security tools and data . He has also been involved in development of the Qradar based User Behavior Analytics Application for detecting insider threats. Before joining the development role Moazzam was involved with the Watson for Cyber Security group as a researcher for another Qradar based application called Watson Advisor. He has also worked with the engineering team for IBM’s IPS and IDS solutions such as G, GX, M and XGS series. He holds a doctorate from Georgia Institute of Technology in Electrical and Computer Engineering. He regularly writes for SecurityIntelligence.com on topics related to cyber security and data science. He is also an adjunct faculty at Kennesaw State University. In his leisure he is a tennis aficionado and participates in several Atlanta based tennis leagues.