Improving self defense by learning from limited experience

In this chapter, we leverage reinforcement learning as a unified framework to design effective adaptive cyber defenses against zero-day attacks. Reinforcement learning is an integration of control theory and machine learning. A salient feature of ...

Previous works have shown that automatic speaker verification (ASV) is seriously vulnerable to malicious spoofing attacks, such as replay, synthetic speech, and recently emerged adversarial attacks. Great efforts have been dedicated to defending ASV ...

Denial of service (DoS) attacks are a serious security threat for Internet based organisations, and effective methods are needed to detect an attack and defend the nodes being attacked in real time. We propose an autonomic approach to DoS defence based ...