Building on the success of the previous years event, we hope you will join us again for the Machine Learning and Cyber Security Symposium (ML-CSS) for 2024.

This symposium is composed of lightning talks by researchers at Imperial who work in the intersection of machine learning and cyber security. The talks should be about a current applied ML&Security research, which will be followed by brief Q&A, within a 15-minute slot. If you are interested in sharing your current work please fill the form (Registration for Speakers). You should submit a topic title, key words, and an abstract (no more than 500 words).

Topics of interest include, but are not limited to:

• ML for Security Applications: Malware Classification, Intrusion Detection, Spam Detection, etc.
• Security-related ML problems: Privacy-preserving data mining, ML approaches to Trust and Reputation, Security incidents generation using ML.
• Applied Adversarial Machine Learning: Causative Attacks (e.g dataset poisoning), Exploratory Attacks (e.g adversarial inputs, prompt injection), and ML Defensive techniques (e.g Adversarial training)
• ML-based Security Applications’ Challenges: Concept Drift, Few-Shot Learning, etc

For the latest details check out our website: http://ml-css.cybersec.fun/