10:00 - 13:00
Artificial intelligence (AI) and Machine learning (ML) has become a vital technology for cybersecurity. Machine learning preemptively stamps out cyber threats and bolsters security infrastructure through pattern detection, real-time cyber crime mapping and thorough penetration testing.
In this workshop, we present different practical Machine learning methods and techniques for (1) the security and dependability of networks, systems, and software, (2) open-source threat intelligence and cybersecurity situational awareness, (3) data security and privacy, (4) cybersecurity forensic analysis, (5) the development of smarter security control, (6) the fight against (cyber)crime, e.g., biometrics, audio/image/video analytics vulnerability analysis (7) malware, anomaly, and intrusion detection, (8) Adversarial machine learning and the robustness of AI models against malicious actions.
Also, we cover Interpretability and Explainability of machine learning models in cybersecurity, Privacy preserving machine learning, Trusted machine learning, Data-centric security, Deep learning for automated recognition of novel threats, Graph representation learning in cybersecurity, and User and entity behavior modeling and analysis.