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All Outputs (9)

A Difficulty in Trust Modelling (2023)
Conference Proceeding
Muller, T. (2023). A Difficulty in Trust Modelling.

There are various trust models, and no pair are the same. Why is there no consensus on what the best trust model is yet? In this paper, we prove some impossibility results, that suggests that no perfect trust model exists. We provide a general meta-m... Read More about A Difficulty in Trust Modelling.

Pre-Signature Scheme for Trustworthy Offline V2V Communication (2023)
Conference Proceeding
Muller, T., Carpent, X., Furnell, S., Almani, D., & Yoshizawa, T. (2023). Pre-Signature Scheme for Trustworthy Offline V2V Communication.

Vehicle-to-Vehicle (V2V) communication systems hold great potential for enhancing road safety and traffic efficiency. The authenti-cation of such communication is crucial, particularly in scenarios where infrastructure is absent, while also ensuring... Read More about Pre-Signature Scheme for Trustworthy Offline V2V Communication.

Stability of Weighted Majority Voting under Estimated Weights (2023)
Conference Proceeding
Bai, S., Wang, D., Muller, T., Cheng, P., & Chen, J. (2023). Stability of Weighted Majority Voting under Estimated Weights. In AAMAS ’23: Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems. https://doi.org/10.5555/3545946.3599045

Weighted Majority Voting (WMV) is a well-known optimal decision rule for collective decision making, given the probability of sources to provide accurate information (trustworthiness). However, in reality, the trustworthiness is not a known quantity... Read More about Stability of Weighted Majority Voting under Estimated Weights.

Provably Robust Decisions based on Potentially Malicious Sources of Information (2020)
Conference Proceeding
Muller, T., Wang, D., & Sun, J. (2020). Provably Robust Decisions based on Potentially Malicious Sources of Information. In 2020 IEEE 33rd Computer Security Foundations Symposium (CSF) (411-425). https://doi.org/10.1109/csf49147.2020.00036

Sometimes a security-critical decision must be made using information provided by peers. Think of routing messages, user reports, sensor data, navigational information, blockchain updates. Attackers manifest as peers that strategically report fake in... Read More about Provably Robust Decisions based on Potentially Malicious Sources of Information.

The Reputation Lag Attack (2019)
Conference Proceeding
Sirur, S., & Muller, T. (2019). The Reputation Lag Attack

Reputation systems and distributed networks are increasingly common. Examples are electronic marketplaces, IoT and ad-hoc networks. The propagation of information through such networks may suffer delays due to, e.g., network connectivity, slow report... Read More about The Reputation Lag Attack.

Is It Harmful when Advisors Only Pretend to Be Honest? (2016)
Conference Proceeding
Wang, D., Muller, T., Zhang, J., & liu, Y. (2016). Is It Harmful when Advisors Only Pretend to Be Honest?. In AAAI'16: Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, (2551--2557)

Using Information Theory to Improve the Robustness of Trust Systems (2015)
Conference Proceeding
Wang, D., Muller, T., Irissappane, A. A., Zhang, J., & Liu, Y. (2015). Using Information Theory to Improve the Robustness of Trust Systems. In AAMAS '15: Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems, (791--799). https://doi.org/10.5555/2772879.2773255

Unfair rating attacks to trust systems can affect the accuracy of trust evaluation when trust ratings (recommendations) about trustee agents are sought by truster agents from others (advisor agents). A robust trust system should remain accurate, even... Read More about Using Information Theory to Improve the Robustness of Trust Systems.

The Fallacy of Endogenous Discounting of Trust Recommendations (2015)
Conference Proceeding
Muller, T., Liu, Y., & Zhang, J. (2015). The Fallacy of Endogenous Discounting of Trust Recommendations. In Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems, (563-572). https://doi.org/10.5555/2772879.2772951

Recommendations are widely used in recommender systems, reputation systems, and trust-based security systems. Some existing reputation systems and trust-based security systems use the flawed notion of endogenous discounting. Endogenous discounting is... Read More about The Fallacy of Endogenous Discounting of Trust Recommendations.

Quantifying robustness of trust systems against collusive unfair rating attacks using information theory (2015)
Conference Proceeding
Wang, D., Muller, T., Zhang, J., & Liu, Y. (2015). Quantifying robustness of trust systems against collusive unfair rating attacks using information theory. In IJCAI'15: Proceedings of the 24th International Conference on Artificial Intelligence. , (111-117)

Unfair rating attacks happen in existing trust and reputation systems, lowering the quality of the systems. There exists a formal model that measures the maximum impact of independent attackers [Wang et al., 2015] - based on information theory. We im... Read More about Quantifying robustness of trust systems against collusive unfair rating attacks using information theory.