Machine learning is increasingly applied in the cybersecurity domain in order to build solutions capable of protecting against attacks that escape rule-based systems. Attacks are nowadays constantly evolving, since adversaries are always creating new approaches or tweaking existing ones: it is thus not possible to rely exclusively on supervised techniques. This talk will focus on the role of anomaly detection techniques in real-world security applications, and how explainability is necessary in order to translate the anomalies detected by the system into actionable events.

PS: If you are landing here for the first time, to stay up to date with the next events join our GDSC community (800+ members) by clicking the 'Join us' button.