This SoK model federated learning as an append-only transcript of submissions, admissions, aggregation, and finalization events, and formalize verifiability as a collection of integrity claims issued by clients and the aggregator, and checked by different verifier classes.
Andrea Rizzini, Marco Esposito, Tommaso Gagliardoni et al.· Proceedings on Privacy Enhan...· 0 citations
VeriProv is proposed, a provenance-based framework for enforcing and auditing non-repudiable and verifiable ML workflows in adversarial cloud environments.
D. Ferreira, Luís E. T. Rodrigues, Nuno Santos· 0 citations
The threat model in the HPC setting is defined, attack surfaces created by schedulers, shared storage, multi-project accounts, and scientific workflows are identified, and where current controls fall short is examined.
A novel audit protocol designed to significantly increase the post-audit detectability of manipulations by enabling the auditor to query the model in an oblivious manner and providing theoretical guarantees showing that, under this protocol, a provider attempting to hide unfairness must falsify a significantly larger n...
Augustin Godinot, Sofiane Azogagh, Julien Ferry et al.· 0 citations
An underexplored threat in which a dishonest orchestrator intentionally manipulates the aggregation process to induce targeted overfitting in local models of specific clients is studied, demonstrating that client-side integrity testing can provide early, effective, and scalable detection, supporting safer deployment of...
Soumia Zohra El Mestari, M. Zuziak, Gabriele Lenzini· Proceedings on Privacy Enhan...· 0 citations
Artificial intelligence (AI) systems are increasingly deployed in high-stakes domains, where poisoning attacks can corrupt training data, manipulate model updates, or implant covert backdoors. This survey examines poisoning attacks in federated learning (FL), using centralized learning as a baseline to explain how dist...
S. Mohammed, D. Alhadidi, A. Ngom· Journal of Cybersecurity and...· 0 citations
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