This study leverages reinforcement learning techniques to identify optimal strategies for cyber defense. These techniques are applied within a cybersecurity game framework, resulting in a continuous, adversarial decision-making scenario between two agents – an attacker and a defender. The findings offer valuable insights for defenders aiming to protect data from cyber threats.
Critical success factors for security education, training and awareness (SETA) programme effectiveness: an empirical comparison of practitioner perspectives
Cyber security has never been more important than it is today in an ever more connected and pervasive digital world....