{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T03:15:19Z","timestamp":1769915719695,"version":"3.49.0"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643686318","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,10,21]],"date-time":"2025-10-21T00:00:00Z","timestamp":1761004800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,10,21]]},"abstract":"<jats:p>Federated Learning (FL) is widely recognized as a privacy-preserving Machine Learning paradigm due to its model-sharing mechanism that avoids direct data exchange. Nevertheless, model training leaves exploitable traces that can be used to infer sensitive information. In Decentralized FL (DFL), the topology, defining how participants are connected, plays a crucial role in shaping the model\u2019s privacy, robustness, and convergence. However, the topology introduces an unexplored vulnerability: attackers can exploit it to infer participant relationships and launch targeted attacks. This work uncovers the hidden risks of DFL topologies by proposing a novel Topology Inference Attack that infers the topology solely from model behavior. A taxonomy of topology inference attacks is introduced, categorizing them by the attacker\u2019s capabilities and knowledge. Practical attack strategies are designed for various scenarios, and experiments are conducted to identify key factors influencing attack success. The results demonstrate that analyzing only the model of each node can accurately infer the DFL topology, highlighting a critical privacy risk in DFL systems. These findings offer insights for improving privacy preservation in DFL environments.<\/jats:p>","DOI":"10.3233\/faia251333","type":"book-chapter","created":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T09:58:25Z","timestamp":1761127105000},"source":"Crossref","is-referenced-by-count":1,"title":["From Models to Network Topologies: A Topology Inference Attack in Decentralized Federated Learning"],"prefix":"10.3233","author":[{"given":"Chao","family":"Feng","sequence":"first","affiliation":[{"name":"Communication Systems Group, Department of Informatics, University of Zurich, CH\u20138050 Z\u00fcrich, Switzerland"}]},{"given":"Yuanzhe","family":"Gao","sequence":"additional","affiliation":[{"name":"Communication Systems Group, Department of Informatics, University of Zurich, CH\u20138050 Z\u00fcrich, Switzerland"}]},{"given":"Alberto","family":"Huertas Celdr\u00e1n","sequence":"additional","affiliation":[{"name":"Communication Systems Group, Department of Informatics, University of Zurich, CH\u20138050 Z\u00fcrich, Switzerland"},{"name":"Department of Information and Communications Engineering, University of Murcia, 30100\u2013Murcia, Spain"}]},{"given":"G\u00e9r\u00f4me","family":"Bovet","sequence":"additional","affiliation":[{"name":"Cyber-Defence Campus, armasuisse Science & Technology, CH\u20133602 Thun, Switzerland"}]},{"given":"Burkhard","family":"Stiller","sequence":"additional","affiliation":[{"name":"Communication Systems Group, Department of Informatics, University of Zurich, CH\u20138050 Z\u00fcrich, Switzerland"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","ECAI 2025"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA251333","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T09:58:26Z","timestamp":1761127106000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA251333"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,21]]},"ISBN":["9781643686318"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia251333","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,21]]}}}