{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,19]],"date-time":"2025-11-19T07:11:38Z","timestamp":1763536298897,"version":"3.28.0"},"reference-count":26,"publisher":"IEEE","license":[{"start":{"date-parts":[[2024,9,2]],"date-time":"2024-09-02T00:00:00Z","timestamp":1725235200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,9,2]],"date-time":"2024-09-02T00:00:00Z","timestamp":1725235200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100007707","name":"INAIL","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100007707","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,9,2]]},"DOI":"10.1109\/csr61664.2024.10679472","type":"proceedings-article","created":{"date-parts":[[2024,9,24]],"date-time":"2024-09-24T17:21:51Z","timestamp":1727198511000},"page":"664-669","source":"Crossref","is-referenced-by-count":2,"title":["A Novel Approach for Securing Federated Learning: Detection and Defense Against Model Poisoning Attacks"],"prefix":"10.1109","author":[{"given":"Giovanni Maria","family":"Cristiano","sequence":"first","affiliation":[{"name":"University of Naples ‘Parthenope’ Centro Direzionale,Napoli,Italy,80133"}]},{"given":"Salvatore","family":"D'Antonio","sequence":"additional","affiliation":[{"name":"University of Naples ‘Parthenope’ Centro Direzionale,Napoli,Italy,80133"}]},{"given":"Federica","family":"Uccello","sequence":"additional","affiliation":[{"name":"University of Naples ‘Parthenope’ Centro Direzionale,Napoli,Italy,80133"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1186\/s13174-018-0087-2"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/3436755"},{"key":"ref3","first-page":"1273","volume":"54","author":"McMahan","year":"2017","journal-title":"Communication-Efficient Learning of Deep Networks from Decentralized Data"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3013541"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3075203"},{"key":"ref6","article-title":"Analyzing federated learning through an adversarial lens","volume":"abs\/1811.12470","author":"Bhagoji","year":"2018","journal-title":"CoRR"},{"key":"ref7","article-title":"Data poisoning against differentially-private learners: Attacks and defenses","volume":"abs\/1903.09860","author":"Ma","year":"2019","journal-title":"CoRR"},{"key":"ref8","volume":"30","author":"Blanchard","year":"2017","journal-title":"Machine learning with adversaries: Byzantine tolerant gradient descent"},{"key":"ref9","first-page":"1605","article-title":"Local model poisoning attacks to Byzantine-Robust federated learning","volume-title":"29th USENIX Security Symposium (USENIX Security 20). USENIX Association","author":"Fang","year":"2020"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2022.3216981"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2023.3238823"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICPADS47876.2019.00042"},{"key":"ref13","first-page":"1846","volume":"130","author":"Fraboni","year":"2021","journal-title":"Free-rider attacks on model aggregation in federated learning"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW56347.2022.00383"},{"key":"ref15","article-title":"Desmp: Differential privacy-exploited stealthy model poisoning attacks in federated learning","volume":"abs\/2109.09955","author":"Hossain","year":"2021","journal-title":"CoRR"},{"key":"ref16","article-title":"Federated learning of deep networks using model averaging","volume":"abs\/1602.05629","author":"McMahan","year":"2016","journal-title":"CoRR"},{"key":"ref17","first-page":"5650","volume":"80","author":"Yin","year":"2018","journal-title":"Byzantine-robust distributed learning: Towards optimal statistical rates"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2022.09.011"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3539231"},{"key":"ref20","first-page":"508","volume-title":"Auror: defending against poisoning attacks in collaborative deep learning systems","author":"Shen","year":"2016"},{"key":"ref21","article-title":"MANDERA: malicious node detection in federated learning via ranking","volume":"abs\/2110.11736","author":"Zhu","year":"2021","journal-title":"CoRR"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TNSE.2020.3002796"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2017.10.013"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2022.11.139"},{"issue":"34","key":"ref26","first-page":"226","article-title":"A density-based algorithm for discovering clusters in large spatial databases with noise","volume":"96","author":"Ester","year":"1996","journal-title":"kdd"}],"event":{"name":"2024 IEEE International Conference on Cyber Security and Resilience (CSR)","start":{"date-parts":[[2024,9,2]]},"location":"London, United Kingdom","end":{"date-parts":[[2024,9,4]]}},"container-title":["2024 IEEE International Conference on Cyber Security and Resilience (CSR)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/10679369\/10679342\/10679472.pdf?arnumber=10679472","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,25]],"date-time":"2024-09-25T05:00:00Z","timestamp":1727240400000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10679472\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9,2]]},"references-count":26,"URL":"https:\/\/doi.org\/10.1109\/csr61664.2024.10679472","relation":{},"subject":[],"published":{"date-parts":[[2024,9,2]]}}}