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Provably Secure Decisions based on Potentially Malicious Information

Wang, Dongxia; Muller, Tim; Sun, Jun

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Authors

Dongxia Wang

TIM MULLER Tim.Muller@nottingham.ac.uk
Assistant Professor

Jun Sun



Contributors

TIM MULLER Tim.Muller@nottingham.ac.uk
Project Leader

Dongxia Wang
Project Member

Abstract

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 decisions based on information from peers, which assume peers may be mistaken with some probability. We focus on attackers in a system, which manifest as peers that strategically report fake information to manipulate decision-making. We define the property of robustness: a lower bound probability of deciding correctly, regardless of what information attackers provide. When peers are independently selected, we propose an optimal, robust decision mechanism called Most Probable Realisation (MPR). When peer collusion affects source selection, we prove that generally, it is NP-hard to find an optimal decision scheme. We propose multiple heuristic decision schemes that can achieve optimality for some collusion scenarios.

Citation

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

Journal Article Type Article
Acceptance Date Dec 19, 2023
Online Publication Date Jan 12, 2024
Publication Date 2024-09
Deposit Date Dec 19, 2023
Publicly Available Date Jan 3, 2024
Journal IEEE Transactions on Dependable and Secure Computing
Print ISSN 1545-5971
Electronic ISSN 1941-0018
Publisher Institute of Electrical and Electronics Engineers
Peer Reviewed Peer Reviewed
Volume 21
Issue 5
Pages 4388-4403
DOI https://doi.org/10.1109/TDSC.2024.3353295
Keywords Multi-source decision making; Provable decision making; Malicious feedback; Collusion attacks; Trust evaluation
Public URL https://nottingham-repository.worktribe.com/output/28708498
Publisher URL https://ieeexplore.ieee.org/document/10398454

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