{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T12:57:17Z","timestamp":1776085037526,"version":"3.50.1"},"reference-count":25,"publisher":"IEEE","license":[{"start":{"date-parts":[[2023,9,12]],"date-time":"2023-09-12T00:00:00Z","timestamp":1694476800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,9,12]],"date-time":"2023-09-12T00:00:00Z","timestamp":1694476800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100013209","name":"Hellenic Foundation for Research and Innovation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100013209","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,9,12]]},"DOI":"10.1109\/etfa54631.2023.10275578","type":"proceedings-article","created":{"date-parts":[[2023,10,12]],"date-time":"2023-10-12T17:38:14Z","timestamp":1697132294000},"page":"1-4","source":"Crossref","is-referenced-by-count":12,"title":["Federated Learning in Malware Detection"],"prefix":"10.1109","author":[{"given":"Dimitrios","family":"Serpanos","sequence":"first","affiliation":[{"name":"University of Patras,Computer Technology Institute and Press DIOPHANTUS & Dept. of Electrical and Computer Engineering,Patras,Greece"}]},{"given":"Georgios","family":"Xenos","sequence":"additional","affiliation":[{"name":"University of Patras Campus,Computer Technology Institute and Press DIOPHANTUS,Patras,Greece"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2023.3235389"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2021.3119038"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2021.3077803"},{"key":"ref14","first-page":"756","article-title":"DÏoT: A Federated Self-learning Anomaly Detection System for IoT","author":"nguyen","year":"2019","journal-title":"Proceedings IEEE 39th International Conference on Distributed Computing Systems (ICDCS)"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/IOTM.004.2100182"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1561\/9781680837896"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-73951-9_2"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.3390\/app11072980"},{"key":"ref17","article-title":"FLAD: Adaptive Federated Learning for DDoS Attack Detection","author":"doriguzzi-corin","year":"2022"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ICDCS47774.2020.00171"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/AsiaJCIS50894.2020.00031"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.2478\/popets-2021-0062"},{"key":"ref24","article-title":"PyTorch: An Imperative Style, High-Performance Deep Learning Library","author":"paszke","year":"2019"},{"key":"ref23","article-title":"Flower: A Friendly Federated Learning Research Framework","author":"beutel","year":"2022"},{"key":"ref25","article-title":"VirusTotal","year":"0"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.comnet.2021.108693"},{"key":"ref22","article-title":"EMBER: An Open Dataset for Training Static PE Malware Machine Learning Models","author":"anderson","year":"2018"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/ICISC44355.2019.9036424"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i11.17131"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2906934"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.cie.2020.106854"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.cose.2015.04.001"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/ACSAC.2007.21"},{"key":"ref6","article-title":"Random Forest for Malware Classification","author":"garcia","year":"2016"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/CSCloud.2015.50"}],"event":{"name":"2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA)","location":"Sinaia, Romania","start":{"date-parts":[[2023,9,12]]},"end":{"date-parts":[[2023,9,15]]}},"container-title":["2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10275065\/10275329\/10275578.pdf?arnumber=10275578","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,30]],"date-time":"2023-10-30T18:44:23Z","timestamp":1698691463000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10275578\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,9,12]]},"references-count":25,"URL":"https:\/\/doi.org\/10.1109\/etfa54631.2023.10275578","relation":{},"subject":[],"published":{"date-parts":[[2023,9,12]]}}}