{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T16:54:43Z","timestamp":1781283283887,"version":"3.54.1"},"reference-count":77,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"5","license":[{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"Ajman University Internal Research","award":["2024-IRG-ENIT-1"],"award-info":[{"award-number":["2024-IRG-ENIT-1"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Sustain. Comput."],"published-print":{"date-parts":[[2025,9]]},"DOI":"10.1109\/tsusc.2025.3570096","type":"journal-article","created":{"date-parts":[[2025,5,14]],"date-time":"2025-05-14T13:34:19Z","timestamp":1747229659000},"page":"1007-1018","source":"Crossref","is-referenced-by-count":3,"title":["Novel Stealth Communication Round Attack and Robust Incentivized Federated Averaging for Load Forecasting"],"prefix":"10.1109","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0192-7353","authenticated-orcid":false,"given":"Habib Ullah","family":"Manzoor","sequence":"first","affiliation":[{"name":"James Watt School of Engineering, University of Glasgow, Glasgow, U.K."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4447-8335","authenticated-orcid":false,"given":"Kamran","family":"Arshad","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, College of Engineering and Information Technology, Ajman University, Ajman, UAE"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0942-0453","authenticated-orcid":false,"given":"Khaled","family":"Assaleh","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, College of Engineering and Information Technology, Ajman University, Ajman, UAE"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7497-9336","authenticated-orcid":false,"given":"Ahmed","family":"Zoha","sequence":"additional","affiliation":[{"name":"James Watt School of Engineering, University of Glasgow, Glasgow, U.K."}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/59.801894"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.3390\/en11030596"},{"key":"ref3","article-title":"IBM security X-force threat intelligence index","author":"Worley","year":"2023"},{"key":"ref4","article-title":"Some of the biggest cyberattacks on energy infrastructure in recent years","author":"Sasibhooshan"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijforecast.2017.08.004"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/3307772.3328314"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/mce.2024.3500579"},{"key":"ref8","first-page":"2938","article-title":"How to backdoor federated learning","volume-title":"Proc. Int. Conf. Artif. Intell. Statist.","author":"Bagdasaryan"},{"key":"ref9","first-page":"16070","article-title":"Attack of the tails: Yes, you really can backdoor federated learning","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Wang"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/BigData55660.2022.10020431"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1186\/s42400-021-00105-6"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2021.3095077"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.3390\/fi16100374"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TDSC.2020.2986205"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.comnet.2022.109094"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2022.03.025"},{"issue":"23","key":"ref17","article-title":"A privacy and energy-aware federated framework for human activity recognition","volume-title":"Sensors","volume":"23","author":"Khan","year":"2023"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/GECOST60902.2024.10475064"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ICC.2019.8761422"},{"key":"ref20","first-page":"634","article-title":"Analyzing federated learning through an adversarial lens","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Bhagoji"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TDSC.2022.3168556"},{"key":"ref22","first-page":"26429","article-title":"Neurotoxin: Durable backdoors in federated learning","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Zhang"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/MNET.011.2000783"},{"key":"ref24","article-title":"Can you really backdoor federated learning?","author":"Sun","year":"2019"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/PIMRC56721.2023.10293950"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2023.107166"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.emnlp-main.6"},{"key":"ref28","first-page":"8632","article-title":"A little is enough: Circumventing defenses for distributed learning","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Baruch"},{"issue":"10","key":"ref29","article-title":"Privacy and security issues in machine learning systems: A survey","volume":"56","author":"Heyz","year":"2019","journal-title":"J. Comput. Res. Develop."},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2020.2988575"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3539231"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2023.3295949"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/MNET.117.2200065"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.14722\/ndss.2022.23156"},{"key":"ref35","first-page":"1415","article-title":"FLAME: Taming backdoors in federated learning","volume-title":"Proc. 31st USENIX Secur. Symp.","author":"Nguyen"},{"key":"ref36","first-page":"119","article-title":"Machine learning with adversaries: Byzantine tolerant gradient descent","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Blanchard"},{"key":"ref37","article-title":"Mitigating sybils in federated learning poisoning","author":"Fung","year":"2018"},{"key":"ref38","article-title":"Learning to detect malicious clients for robust federated learning","author":"Li","year":"2020"},{"key":"ref39","first-page":"508","article-title":"AUROR: Defending against poisoning attacks in collaborative deep learning systems","volume-title":"Proc. 32nd Annu. Conf. Comput. Secur. Appl.","author":"Shen"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP40776.2020.9054676"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58951-6_24"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/ICDCS51616.2021.00086"},{"key":"ref43","first-page":"12613","article-title":"FL-WBC: Enhancing robustness against model poisoning attacks in federated learning from a client perspective","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Sun"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i10.17118"},{"key":"ref45","article-title":"Backdoor attacks on federated meta-learning","author":"Chen","year":"2020"},{"key":"ref46","article-title":"Mitigating backdoor attacks in federated learning","author":"Wu","year":"2020"},{"key":"ref47","first-page":"11372","article-title":"CRFL: Certifiably robust federated learning against backdoor attacks","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Xie"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1145\/3488932.3517395"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/ICECS202256217.2022.9970909"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/TBDATA.2022.3192121"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/TNSE.2020.3002796"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-38991-8_39"},{"key":"ref53","article-title":"Enhanced adversarial attack resilience in energy networks through energy and privacy aware federated learning","author":"Manzoor","year":"2024","journal-title":"Authorea Preprints"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1016\/j.enbuild.2024.114871"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1016\/j.cie.2020.106854"},{"key":"ref56","first-page":"1273","article-title":"Communication-efficient learning of deep networks from decentralized data","volume-title":"Proc. Int. Conf. Artif. Intell. Statist.","author":"McMahan"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/TPDS.2021.3090331"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/TDSC.2020.3021008"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.4018\/AISPE"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1109\/TDSC.2021.3135422"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.14722\/ndss.2021.24498"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2022.110178"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1145\/272991.272995"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-020-09092-1"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.3390\/rs12111893"},{"key":"ref66","first-page":"607","article-title":"Formal verification and code-generation of Mersenne-Twister algorithm","volume-title":"Proc. Int. Symp. Inf. Theory Appl.","author":"Saikawa"},{"key":"ref67","article-title":"Hourly energy consumption","author":"Mulla"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.3390\/s23073570"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1016\/j.iot.2024.101376"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i7.26083"},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.1109\/VTS-APWCS.2019.8851649"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2019.2894944"},{"key":"ref73","doi-asserted-by":"publisher","DOI":"10.1109\/iThings\/GreenCom\/CPSCom\/SmartData.2019.00148"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2020.2967772"},{"key":"ref75","volume-title":"Games and Information: An Introduction to Game Theory","author":"Rasmusen","year":"1990"},{"key":"ref76","first-page":"3521","article-title":"The hidden vulnerability of distributed learning in Byzantium","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Guerraoui"},{"key":"ref77","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.3015958"}],"container-title":["IEEE Transactions on Sustainable Computing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/7274860\/11197867\/11004057.pdf?arnumber=11004057","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T17:38:28Z","timestamp":1760117908000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11004057\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9]]},"references-count":77,"journal-issue":{"issue":"5"},"URL":"https:\/\/doi.org\/10.1109\/tsusc.2025.3570096","relation":{"has-preprint":[{"id-type":"doi","id":"10.36227\/techrxiv.174741589.98032276\/v1","asserted-by":"object"}]},"ISSN":["2377-3782","2377-3790"],"issn-type":[{"value":"2377-3782","type":"electronic"},{"value":"2377-3790","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,9]]}}}