Autonomous agents require trust and reputation concepts in order to identify communities of agents with which to interact reliably in ways analogous to humans. This paper defines a class of attacks called witness-based collusion attacks designed to exploit trust and reputation models. Empirical results demonstrate that unidimensional trust models are vulnerable to witness-based collusion attacks while independent multidimensional trust models are not. The paper demonstrates that here is a need for witness interaction trust to detect colluding agents in addition to the need for direct interaction trust to detect malicious agents. By proposing a set of policies, the paper demonstrates how learning agents can decrease the level of encounter risk in a witness-based collusive society.

Additional Metadata
Keywords Collusion, Reputation, Trust, Trust-aware societies, Witness-based collusion
Persistent URL dx.doi.org/10.1109/CSE.2009.305
Conference 2009 IEEE International Conference on Social Computing, SocialCom 2009
Citation
Salehi-Abari, A. (Amirali), & White, A. (2009). Witness-based collusion and trust-aware societies. In Proceedings - 12th IEEE International Conference on Computational Science and Engineering, CSE 2009 (pp. 1008–1014). doi:10.1109/CSE.2009.305