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Syst."],"published-print":{"date-parts":[[2024,5,21]]},"abstract":"<jats:p>Federated Learning (FL) permits different parties to collaboratively train a global model without disclosing their respective local labels. A crucial step of FL, that of aggregating local models to produce the global one, shares many similarities with public decision-making, and elections in particular. In that context, a major weakness of FL, namely its vulnerability to poisoning attacks, can be interpreted as a consequence of the one person one vote (henceforth 1p1v) principle that underpins most contemporary aggregation rules. In this paper, we introduce FedQV, a novel aggregation algorithm built upon the quadratic voting scheme, recently proposed as a better alternative to 1p1v-based elections. Our theoretical analysis establishes that FedQV is a truthful mechanism in which bidding according to one's true valuation is a dominant strategy that achieves a convergence rate matching that of state-of-the-art methods. Furthermore, our empirical analysis using multiple real-world datasets validates the superior performance of FedQV against poisoning attacks. It also shows that combining FedQV with unequal voting \"budgets'' according to a reputation score increases its performance benefits even further. Finally, we show that FedQV can be easily combined with Byzantine-robust privacy-preserving mechanisms to enhance its robustness against both poisoning and privacy attacks.<\/jats:p>","DOI":"10.1145\/3656006","type":"journal-article","created":{"date-parts":[[2024,5,29]],"date-time":"2024-05-29T10:40:32Z","timestamp":1716979232000},"page":"1-36","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["FedQV: Leveraging Quadratic Voting in Federated Learning"],"prefix":"10.1145","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2178-840X","authenticated-orcid":false,"given":"Tianyue","family":"Chu","sequence":"first","affiliation":[{"name":"IMDEA Networks Institute &amp; Universidad Carlos III of Madrid, Madrid, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7361-106X","authenticated-orcid":false,"given":"Nikolaos","family":"Laoutaris","sequence":"additional","affiliation":[{"name":"IMDEA Networks Institute, Madrid, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2024,5,29]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Distributed systems: methods and tools for specification. 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