Skip to main content

Research Repository

Advanced Search

All Outputs (14)

Enabling Vehicle-to-Vehicle Trust in Rural Areas: An Evaluation of a Pre-Signature Scheme for Infrastructure-Limited Environments (2024)
Journal Article
Almani, D., Muller, T., Carpent, X., Yoshizawa, T., & Furnell, S. (2024). Enabling Vehicle-to-Vehicle Trust in Rural Areas: An Evaluation of a Pre-Signature Scheme for Infrastructure-Limited Environments. Future Internet, 16(3), Article 77. https://doi.org/10.3390/fi16030077

This research investigates the deployment and effectiveness of the novel Pre-Signature scheme, developed to allow for up-to-date reputation being available in Vehicle-to-Vehicle (V2V) communications in rural landscapes, where the communications infra... Read More about Enabling Vehicle-to-Vehicle Trust in Rural Areas: An Evaluation of a Pre-Signature Scheme for Infrastructure-Limited Environments.

Provably Secure Decisions based on Potentially Malicious Information (2024)
Journal Article
Wang, D., Muller, T., & Sun, J. (2024). Provably Secure Decisions based on Potentially Malicious Information. IEEE Transactions on Dependable and Secure Computing, 21(5), 4388-4403. https://doi.org/10.1109/TDSC.2024.3353295

There are various security-critical decisions routinely made, based on information provided by peers: routing messages, user reports, sensor data, navigational information, blockchain updates, etc. Jury theorems were proposed in sociology to make dec... Read More about Provably Secure Decisions based on Potentially Malicious Information.

A Difficulty in Trust Modelling (2023)
Presentation / Conference Contribution
Muller, T. (2023, October). A Difficulty in Trust Modelling. Presented at 14th IFIP International Conference on Trust Management (IFIPTM 2023), Amsterdam, Netherlands

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)
Presentation / Conference Contribution
Muller, T., Carpent, X., Furnell, S., Almani, D., & Yoshizawa, T. (2023, October). Pre-Signature Scheme for Trustworthy Offline V2V Communication. Presented at 14th IFIP International Conference on Trust Management (IFIPTM 2023), Amsterdam, Netherlands

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)
Presentation / Conference Contribution
Bai, S., Wang, D., Muller, T., Cheng, P., & Chen, J. (2023, May). Stability of Weighted Majority Voting under Estimated Weights. Presented at International Conference on Autonomous Agents and Multiagent Systems (AAMAS 23), London, UK

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.

Simulating the Impact of Personality on Fake News (2021)
Presentation / Conference Contribution
Coates, A., Muller, T., & Sirur, S. Simulating the Impact of Personality on Fake News. Presented at 22nd International Workshop on Trust in Agent Societies (TRUST 2021), London, UK

Fake news is a key issue for social networks. We use an agent-based network simulation to model the spread of (fake) news. The agents' behaviour captures the OCEAN ("big five") personality trait model. The network is homophilic for political preferen... Read More about Simulating the Impact of Personality on Fake News.

Provably Robust Decisions based on Potentially Malicious Sources of Information (2020)
Presentation / Conference Contribution
Muller, T., Wang, D., & Sun, J. (2020, June). Provably Robust Decisions based on Potentially Malicious Sources of Information. Presented at 2020 IEEE 33rd Computer Security Foundations Symposium (CSF), Boston, Massachusetts, USA

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)
Presentation / Conference Contribution
Sirur, S., & Muller, T. (2019, July). The Reputation Lag Attack. Presented at 13th IFIP WG 11.11 International Conference on Trust Management, Copenhagen, Denmark

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.

Information Theoretical Analysis of Unfair Rating Attacks under Subjectivity (2019)
Journal Article
Wang, D., Muller, T., Zhang, J., & Liu, Y. (2019). Information Theoretical Analysis of Unfair Rating Attacks under Subjectivity. IEEE Transactions on Information Forensics and Security, 15, 816-828. https://doi.org/10.1109/TIFS.2019.2929678

Ratings provided by advisors can help an advisee to make decisions, e.g., which seller to select in e-commerce. Unfair rating attacks – where dishonest ratings are provided to mislead the advisee – impact the accuracy of decision making. Current lite... Read More about Information Theoretical Analysis of Unfair Rating Attacks under Subjectivity.

Using Information Theory to Improve the Robustness of Trust Systems (2015)
Presentation / Conference Contribution
Wang, D., Muller, T., Irissappane, A. A., Zhang, J., & Liu, Y. (2015, May). Using Information Theory to Improve the Robustness of Trust Systems. Presented at AAMAS'15: International Conference on Autonomous Agents and Multiagent Systems, Istanbul Turkey

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)
Presentation / Conference Contribution
Muller, T., Liu, Y., & Zhang, J. (2015, May). The Fallacy of Endogenous Discounting of Trust Recommendations. Presented at 2015 International Conference on Autonomous Agents and Multiagent Systems, Istanbul, Turkey

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)
Presentation / Conference Contribution
Wang, D., Muller, T., Zhang, J., & Liu, Y. (2015, July). Quantifying robustness of trust systems against collusive unfair rating attacks using information theory. Presented at International Joint Conferences on Artificial Intelligence, Buenos Aires, Argentina

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.

Expressiveness modulo bisimilarity of regular expressions with parallel composition (2015)
Presentation / Conference Contribution
Luttik, B. A., Baeten, J. C., Muller, T. I., & Van Tilburg, P. (2010, August). Expressiveness modulo bisimilarity of regular expressions with parallel composition. Presented at 17th International Workshop on Expressiveness in Concurrency (EXPRESS'10), Paris, France

© Cambridge University Press 2015. The languages accepted by finite automata are precisely the languages denoted by regular expressions. In contrast, finite automata may exhibit behaviours that cannot be described by regular expressions up to bisimil... Read More about Expressiveness modulo bisimilarity of regular expressions with parallel composition.