By Sheikh Mahbub Habib, Julita Vassileva, Sjouke Mauw, Max Mühlhäuser
This booklet constitutes the refereed court cases of the tenth IFIP WG 11.11 foreign convention on belief administration, IFIPTM 2016, held in Darmstadt, Germany, in July 2016. The 7 revised complete papers and seven brief papers offered including an invited paper have been rigorously reviewed and chosen from 26 submissions. The papers conceal a variety of issues together with belief structure, belief modeling, belief metrics and computation, acceptance and privateness, defense and belief, sociotechnical facets of belief, and assaults on belief and acceptance systems.
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Additional info for Trust Management X: 10th IFIP WG 11.11 International Conference, IFIPTM 2016, Darmstadt, Germany, July 18-22, 2016, Proceedings
Attacks are considered successful, when they achieve some goal. The goal is not known in advance. Since we are considering robustness, we primarily care about the worst-case for a user – the information leakage is minimal. Hence, we pragmatically assert that the goal of an attack is to minimise information leakage. We assume attackers select the strategy that minimises information leakage. If we are wrong, then the information leakage increases by deﬁnition. 1 provides detailed formal analysis.
Using information theory to improve the robustness of trust systems. In: Proceedings of the 14th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 791–799 (2015) 12. : Quantifying robustness of trust systems against collusive unfair rating attacks using information theorys. In: Proceedings of the 24th International Joint Conference on Artiﬁcial Intelligence (IJCAI), pp. 111–117 (2015) 13. : Is it harmful when advisors only pretend to be honest? In: Proceedings of the 30th AAAI Conference on Artiﬁcial Intelligence (2016) 14.
We introduce R and R, both over R, to represent the rating an honest or malicious advisor would give. Thus, Ra = Ra whenever Sa = , and Ra = Ra whenever Sa = ⊥. We shorthand the prior probability that a is honest as P (Sa ) = sa . As we reason about a trust system, we assert 0 < sa < 1. In the running example, we mentioned that the honest advisors’ ratings say something about the best option (decision). We distil that notion by saying Θ is not independent from honest advisors’ ratings A ⊆ A : P (Θ) = P (Θ|RA ).