Challenges in adopting Machine Learning for Cybersecurity

Challenges in adopting Machine Learning for Cybersecurity

Desislava Wagenknecht-Dimitrova

04 May 2022

Machine learning can be a powerful ally in fighting Cybercrime provided that few challenges in its application can be solved. The Keybridge team at Oracle Labs has experience with developing ML solutions for security use cases. In this talk we would like to share those experiences and discuss three challenges - selecting an ML model, handling of input data (specifically system logs) and transferring to security teams. In the latter challenge, we are particularly interested in bridging the two-way gap in understanding between security teams and ML practitioners.


Venue : ZISC lunch seminar (Zurich Information Security and Privacy Centre)

File Name : DimitrovaD_202205_ZISC_MLchallengesForSecurity.pdf