[2411.03231] LOGSAFE: Logic-Guided Verification for Trustworthy Federated Time-Series Learning

Computer Science > Cryptography and Security arXiv:2411.03231 (cs) [Submitted on 5 Nov 2024 (v1), last revised 24 Mar 2026 (this version, v3)] Title:LOGSAFE: Logic-Guided Verification for Trustworthy Federated Time-Series Learning Authors:Dung Thuy Nguyen, Ziyan An, Taylor T. Johnson, Meiyi Ma, Kevin Leach View a PDF of the paper titled LOGSAFE: Logic-Guided Verification for Trustworthy Federated Time-Series Learning, by Dung Thuy Nguyen and 4 other authors View PDF HTML (experimental) Abstract:This paper introduces LOGSAFE, a defense mechanism for federated learning in time series settings, particularly within cyber-physical systems. It addresses poisoning attacks by moving beyond traditional update-similarity methods and instead using logical reasoning to evaluate client reliability. LOGSAFE extracts client-specific temporal properties, infers global patterns, and verifies clients against them to detect and exclude malicious participants. Experiments show that it significantly outperforms existing methods, achieving up to 93.27% error reduction over the next best baseline. Our code is available at this https URL. Comments: Subjects: Cryptography and Security (cs.CR); Artificial Intelligence (cs.AI); Distributed, Parallel, and Cluster Computing (cs.DC); Logic in Computer Science (cs.LO) Cite as: arXiv:2411.03231 [cs.CR]   (or arXiv:2411.03231v3 [cs.CR] for this version)   https://doi.org/10.48550/arXiv.2411.03231 Focus to learn more arXiv-issued DOI via DataCite Submissio...