Cyber-vulnerabilities are being exploited in a growing number of control systems. As many
of these systems form the backbone of critical infrastructure and are becoming more …

We study automated intrusion prevention using reinforcement learning. In a novel approach,
we formulate the problem of intrusion prevention as an optimal stopping problem. This …

We study automated intrusion prevention using reinforcement learning. Following a novel
approach, we formulate the problem of intrusion prevention as an (optimal) multiple stopping …

We study automated intrusion response and formulate the interaction between an attacker
and a defender as an optimal stopping game where attack and defense strategies evolve …

We study automated intrusion prevention using reinforcement learning. Following a novel
approach, we formulate the interaction between an attacker and a defender as an optimal …

The increase in personal devices, the amount of private and sensitive information these
devices store/process, and the importance of this information have introduced vital security …

We are currently facing unprecedented cyber warfare with the rapid evolution of tactics,
increasing asymmetry of intelligence, and the growing accessibility of hacking tools. In this …

This paper studies the agent identity privacy problem in the scalar linear quadratic Gaussian
(LQG) control system. The agent identity is a binary hypothesis: Agent A or Agent B. An …

Evaluating the effectiveness of defense technologies mandates the inclusion of a human
element, specifically if these technologies target human cognition and emotions. One of the …

Cybersecurity is one of the most pressing technological challenges of our time and requires
measures from all sectors of society. A key measure is automated security response, which …