SHERPA: Explainable Robust Algorithms for Privacy-Preserved Federated Learning in Future Networks to Defend Against Data Poisoning Attacks

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: SHERPA: Explainable Robust Algorithms for Privacy-Preserved Federated Learning in Future Networks to Defend Against Data Poisoning Attacks
Συγγραφείς: Sandeepa, Chamara, Siniarski, Bartlomiej, Wang, Shen, Liyanage, Madhusanka
Πηγή: 2024 IEEE Symposium on Security and Privacy (SP) SP Symposium on Security and Privacy (SP), 2024 IEEE. :4772-4790 May, 2024
Relation: 2024 IEEE Symposium on Security and Privacy (SP)
Βάση Δεδομένων: IEEE Xplore Digital Library
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        Value: 10.1109/SP54263.2024.00271
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      – TitleFull: SHERPA: Explainable Robust Algorithms for Privacy-Preserved Federated Learning in Future Networks to Defend Against Data Poisoning Attacks
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