{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,4]],"date-time":"2026-03-04T01:22:03Z","timestamp":1772587323542,"version":"3.50.1"},"reference-count":26,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,6,27]],"date-time":"2022-06-27T00:00:00Z","timestamp":1656288000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,6,27]],"date-time":"2022-06-27T00:00:00Z","timestamp":1656288000000},"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":[[2022,6,27]]},"DOI":"10.1109\/netsoft54395.2022.9844024","type":"proceedings-article","created":{"date-parts":[[2022,8,3]],"date-time":"2022-08-03T19:34:09Z","timestamp":1659555249000},"page":"420-428","source":"Crossref","is-referenced-by-count":14,"title":["FedSA: Accelerating Intrusion Detection in Collaborative Environments with Federated Simulated Annealing"],"prefix":"10.1109","author":[{"given":"Helio N. Cunha","family":"Neto","sequence":"first","affiliation":[{"name":"Universidade Federal Fluminense- Niterói,MídiaCom - PPGEET\/UFF,Brazil"}]},{"given":"Ivana","family":"Dusparic","sequence":"additional","affiliation":[{"name":"School of Computer Science Trinity College Dublin,Dublin,Ireland"}]},{"given":"Diogo M. F.","family":"Mattos","sequence":"additional","affiliation":[{"name":"Universidade Federal Fluminense- Niterói,MídiaCom - PPGEET\/UFF,Brazil"}]},{"given":"Natalia C.","family":"Fernande","sequence":"additional","affiliation":[{"name":"Universidade Federal Fluminense- Niterói,MídiaCom - PPGEET\/UFF,Brazil"}]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2020.2986024"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.3390\/app8122663"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICDCS.2019.00080"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/MNET.011.2000286"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3041793"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/ICDCS.2019.00099"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ICIN.2019.8685888"},{"key":"ref17","first-page":"1","article-title":"Federated learning-based anomaly detection for iot security attacks","author":"mothukuri","year":"2021","journal-title":"IEEE Internet of Things Journal"},{"key":"ref18","article-title":"Federated learning for malware detection in iot devices","author":"rey","year":"2021"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2021.3125137"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/NOMS.2018.8406237"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2019.105124"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/Blockchain50366.2020.00019"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.3390\/app9204396"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/3298981"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CIoT50422.2020.9244289"},{"key":"ref2","doi-asserted-by":"crossref","first-page":"5344e","DOI":"10.1002\/cpe.5344","article-title":"Toward a monitoring and threat detection system based on stream processing as a virtual network function for big data","volume":"31","author":"andreoni lopez","year":"2019","journal-title":"Concurrency and Computation Practice and Experience"},{"key":"ref9","article-title":"Communication-efficient learning of deep networks from decentralized data","volume":"54","author":"brendan mcmahan","year":"2017","journal-title":"Proceedings of the 20th International Conference on Artificial Intelligence and Statistics AISTATS 2017"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1186\/s13174-019-0106-y"},{"key":"ref20","first-page":"4424","article-title":"Federated multi-task learning","author":"smith","year":"2017","journal-title":"Advances in neural information processing systems"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/34.295910"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2019.2904348"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CCST.2019.8888419"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1007\/978-94-015-7744-1_2"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-020-01892-0"},{"key":"ref25","doi-asserted-by":"crossref","first-page":"669","DOI":"10.1109\/72.377972","article-title":"Dynamic learning rate optimization of the backpropagation algorithm","volume":"6","author":"yu","year":"1995","journal-title":"IEEE Transactions on Neural Networks"}],"event":{"name":"2022 IEEE 8th International Conference on Network Softwarization (NetSoft)","location":"Milan, Italy","start":{"date-parts":[[2022,6,27]]},"end":{"date-parts":[[2022,7,1]]}},"container-title":["2022 IEEE 8th International Conference on Network Softwarization (NetSoft)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9844017\/9844019\/09844024.pdf?arnumber=9844024","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,8,22]],"date-time":"2022-08-22T20:02:19Z","timestamp":1661198539000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9844024\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,6,27]]},"references-count":26,"URL":"https:\/\/doi.org\/10.1109\/netsoft54395.2022.9844024","relation":{},"subject":[],"published":{"date-parts":[[2022,6,27]]}}}