{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T05:57:24Z","timestamp":1767333444720,"version":"3.48.0"},"reference-count":25,"publisher":"IEEE","license":[{"start":{"date-parts":[[2025,10,6]],"date-time":"2025-10-06T00:00:00Z","timestamp":1759708800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,10,6]],"date-time":"2025-10-06T00:00:00Z","timestamp":1759708800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,10,6]]},"DOI":"10.1109\/milcom64451.2025.11310198","type":"proceedings-article","created":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T18:35:33Z","timestamp":1767292533000},"page":"820-825","source":"Crossref","is-referenced-by-count":0,"title":["Federated Learning-Based Anomaly Detection Approach for High-Performance Research Networks"],"prefix":"10.1109","author":[{"given":"Ehsan","family":"Saeedizade","sequence":"first","affiliation":[{"name":"University of Nevada, Reno,Department of Computer Science and Engineering,Reno,USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shamik","family":"Sengupta","sequence":"additional","affiliation":[{"name":"University of Nevada, Reno,Department of Computer Science and Engineering,Reno,USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jay","family":"Thom","sequence":"additional","affiliation":[{"name":"University of Nevada, Reno,Department of Computer Science and Engineering,Reno,USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1007\/s10207-022-00584-9"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/MILCOM55135.2022.10017793"},{"key":"ref3","article-title":"Detecting outliers in network transfers with feature extraction","volume-title":"Tech. Rep","author":"Rao","year":"2018"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2022.3150363"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/e-Science58273.2023.10254940"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/PESGM51994.2024.10688634"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CSR61664.2024.10679380"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.3390\/electronics14030410"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-020-05870-y"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/MILCOM.2017.8170749"},{"key":"ref11","article-title":"Machine learning for data transfer anomaly detection","author":"Cooper","year":"2020","journal-title":"IEEE\/ACM Supercomputing"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/EuCNC\/6GSummit60053.2024.10597083"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ICDCS47774.2020.00171"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.3390\/s25010010"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/ICC45041.2023.10278993"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN52387.2021.9533294"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1145\/3078597.3078605"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/e-Science58273.2023.10254871"},{"key":"ref19","first-page":"1273","article-title":"Communication-efficient learning of deep networks from decentralized data","author":"McMahan","year":"2017","journal-title":"Artificial intelligence and statistics"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1201\/9781315139470"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/COMNETSAT59769.2023.10420613"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-54129-2_8"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/INDIS54524.2021.00009"},{"issue":"171","key":"ref24","first-page":"1","article-title":"Feature-level domain adaptation","volume":"17","author":"Kouw","year":"2016","journal-title":"Journal of Machine Learning Research"},{"article-title":"Flower: A friendly federated learning research framework","year":"2020","author":"Beutel","key":"ref25"}],"event":{"name":"MILCOM 2025 - 2025 IEEE Military Communications Conference (MILCOM)","start":{"date-parts":[[2025,10,6]]},"location":"Los Angeles, CA, USA","end":{"date-parts":[[2025,10,10]]}},"container-title":["MILCOM 2025 - 2025 IEEE Military Communications Conference (MILCOM)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11309822\/11309347\/11310198.pdf?arnumber=11310198","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T05:53:25Z","timestamp":1767333205000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11310198\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,6]]},"references-count":25,"URL":"https:\/\/doi.org\/10.1109\/milcom64451.2025.11310198","relation":{},"subject":[],"published":{"date-parts":[[2025,10,6]]}}}