Biblio

The Internet of Battlefield Things (IoBT) might be one of the most expensive cyber-physical systems of the next decade, yet much research remains to develop its fundamental enablers. A challenge that distinguishes the IoBT from its civilian counterparts is resilience to a much larger spectrum of threats.

Incentive-driven advanced attacks have become a major concern to cyber-security. Traditional defense techniques that adopt a passive and static approach by assuming a fixed attack type are insufficient in the face of highly adaptive and stealthy attacks. In particular, a passive defense approach often creates information asymmetry where the attacker knows more about the defender. To this end, moving target defense (MTD) has emerged as a promising way to reverse this information asymmetry. The main idea of MTD is to (continuously) change certain aspects of the system under control to increase the attacker's uncertainty, which in turn increases attack cost/complexity and reduces the chance of a successful exploit in a given amount of time. In this paper, we go one step beyond and show that MTD can be further improved when combined with information disclosure. In particular, we consider that the defender adopts a MTD strategy to protect a critical resource across a network of nodes, and propose a Bayesian Stackelberg game model with the defender as the leader and the attacker as the follower. After fully characterizing the defender's optimal migration strategies, we show that the defender can design a signaling scheme to exploit the uncertainty created by MTD to further affect the attacker's behavior for its own advantage. We obtain conditions under which signaling is useful, and show that strategic information disclosure can be a promising way to further reverse the information asymmetry and achieve more efficient active defense.

The longstanding debate on a fundamental science of security has led to advances in systems, software, and network security. However, existing efforts have done little to inform how an environment should react to emerging and ongoing threats and compromises. The authors explore the goals and structures of a new science of cyber-decision-making in the Cyber-Security Collaborative Research Alliance, which seeks to develop a fundamental theory for reasoning under uncertainty the best possible action in a given cyber environment. They also explore the needs and limitations of detection mechanisms; agile systems; and the users, adversaries, and defenders that use and exploit them, and conclude by considering how environmental security can be cast as a continuous optimization problem.
 

The longstanding debate on a fundamental science of security has led to advances in systems, software, and network security. However, existing efforts have done little to inform how an environment should react to emerging and ongoing threats and compromises. The authors explore the goals and structures of a new science of cyber-decision-making in the Cyber-Security Collaborative Research Alliance, which seeks to develop a fundamental theory for reasoning under uncertainty the best possible action in a given cyber environment. They also explore the needs and limitations of detection mechanisms; agile systems; and the users, adversaries, and defenders that use and exploit them, and conclude by considering how environmental security can be cast as a continuous optimization problem.