Security Decision-making with Private Information

PROJECT PI

Dr. Xiaofan He, Assistant Professor, Phillip M. Drayer Department of Electrical Engineering

SHORT DESCRIPTION

The objective of this project is to examine the potential impact of various of forms of private information to the decision-making process in different security scenarios. Novel algorithms will be developed to facilitate the defender in handling the private information and achieving more efficiency and effective defense against the adversary. Besides from theoretic study, applications to practice will also be considered.

FULL DESCRIPTION

Along the path of human civilization, there has never been a ceasefire in security. Rather, modern technological advancements have made the security competitions more intense and sophisticated than ever before. In view of the adversary’s constant growth in intelligence and escalation in attacking tactics, security solutions solely based on experience and heuristics will no longer be effective and sometimes may even lead to a false sense of security.

To achieve more reliable and effective defense mechanisms in various security problems, it is often of crucial importance to obtain good understandings of the adversary and be able to analyze its possible strategies. Game theory, a set of celebrated mathematical tools for analyzing the strategical interactions among multiple intelligent decision makers, has been widely employed in literature to analyze the security games between the defender and the attacker. However, the private information held by the defender and the attacker in practical security problems makes the corresponding game-theoretic analysis challenging, and how the private information is handled is often the key to the victory in security games. In this project, we plan to explore the private information issue in security decision-making from different perspectives.

FUNDING

The project proposal is still under review

PUBLICATIONS

  • X. He, H. Dai, and P. Ning, “Improving learning and adaptation in security games by exploiting information asymmetry,” in IEEE INFOCOM, 2015.
  • X. He, H. Dai, and P. Ning, “Faster learning and adaptation in security games by exploiting information asymmetry,” IEEE Transactions on Signal Processing, vol. 64, no. 13, pp. 3429–3443, 2015.
  • X. He, H. Dai, P. Ning, and R. Dutta, “A stochastic multi-channel spectrum access game with incomplete information,” in IEEE ICC, 2015.
  • R. Jin, X. He, and H. Dai, “Collaborative IDS configuration: A two-layer game-theoretical approach,” in IEEE GLOBECOM, 2016.
  • X. He, H. Dai, P. Ning, and R. Dutta, “A multi-player Markov stopping game for delay tolerant and opportunistic resource sharing networks,” in IEEE INFOCOM, 2016.