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In this paper, we consider the scenario of compromised and malicious participants in the SL environment, where a participant can manipulate the privacy of other participant in collaborative training. We propose a method, Swarm-FHE, Swarm Learning with Fully Homomorphic Encryption (FHE), to encrypt the model parameters before sharing with the participants which are registered and authenticated by blockchain technology. Each participant shares the encrypted parameters (i.e. ciphertexts) with other participants in SL training. We evaluate our method with training of the convolutional neural networks on the CIFAR-10 and MNIST datasets. On the basis of a considerable number of experiments and results with different hyperparameter settings, our method performs better as compared to other existing methods. <\/jats:p>","DOI":"10.1142\/s0129065723500338","type":"journal-article","created":{"date-parts":[[2023,4,20]],"date-time":"2023-04-20T08:54:22Z","timestamp":1681980862000},"source":"Crossref","is-referenced-by-count":15,"title":["Swarm-FHE: Fully Homomorphic Encryption-based Swarm Learning for Malicious Clients"],"prefix":"10.1142","volume":"33","author":[{"given":"Hussain Ahmad","family":"Madni","sequence":"first","affiliation":[{"name":"Department of Mathematics, Computer Science and Physics (DMIF), University of Udine, Udine 33100, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rao Muhammad","family":"Umer","sequence":"additional","affiliation":[{"name":"Institute of AI for Health, Helmholtz Zentrum M\u00fcnchen \u2014 German Research, Center for Environmental Health, Neuherberg 85764, Germany"},{"name":"Department of Computer Science, University of Engineering and Technology, Lahore 39161, Pakistan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gian Luca","family":"Foresti","sequence":"additional","affiliation":[{"name":"Department of Mathematics, Computer Science and Physics (DMIF), University of Udine, Udine 33100, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2023,5,27]]},"reference":[{"key":"S0129065723500338BIB001","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1016\/j.neucom.2022.04.127","volume":"497","author":"Tian Y.","year":"2022","journal-title":"Neurocomputing"},{"key":"S0129065723500338BIB002","doi-asserted-by":"publisher","DOI":"10.1142\/S0129065716500258"},{"key":"S0129065723500338BIB003","doi-asserted-by":"crossref","first-page":"2350014","DOI":"10.1142\/S0129065723500144","volume":"33","author":"Ding X.","year":"2023","journal-title":"Int. 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