{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,26]],"date-time":"2025-12-26T18:29:20Z","timestamp":1766773760870,"version":"3.48.0"},"reference-count":117,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U24A20336"],"award-info":[{"award-number":["U24A20336"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U22B2022"],"award-info":[{"award-number":["U22B2022"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Liaoning Natural Science Funds","award":["2025-BS-0212"],"award-info":[{"award-number":["2025-BS-0212"]}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100017683","name":"Dalian Science and Technology Innovation Fund","doi-asserted-by":"publisher","award":["2024JB11GX001"],"award-info":[{"award-number":["2024JB11GX001"]}],"id":[{"id":"10.13039\/501100017683","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Netw. Sci. Eng."],"published-print":{"date-parts":[[2026]]},"DOI":"10.1109\/tnse.2025.3626056","type":"journal-article","created":{"date-parts":[[2025,10,28]],"date-time":"2025-10-28T17:36:16Z","timestamp":1761672976000},"page":"4422-4439","source":"Crossref","is-referenced-by-count":0,"title":["LBKD: Rethinking Federated Backdoors for Low-Altitude Economy via LLMs and Bidirectional Knowledge Distillation"],"prefix":"10.1109","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-0742-2946","authenticated-orcid":false,"given":"Haoquan","family":"Wang","sequence":"first","affiliation":[{"name":"Key Laboratory of Aerospace Information Security and Trusted Computing, Ministry of Education, School of Cyber Science and Engineering, Wuhan University, Wuhan, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9306-9303","authenticated-orcid":false,"given":"Boyuan","family":"Li","sequence":"additional","affiliation":[{"name":"School of Computer Science and Artificial Intelligence, Zhengzhou University, Zhengzhou, China"}]},{"given":"Panpan","family":"Chen","sequence":"additional","affiliation":[{"name":"Key Laboratory of Aerospace Information Security and Trusted Computing, Ministry of Education, School of Cyber Science and Engineering, Wuhan University, Wuhan, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9897-1953","authenticated-orcid":false,"given":"Libing","family":"Wu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Aerospace Information Security and Trusted Computing, Ministry of Education, School of Cyber Science and Engineering, Wuhan University, Wuhan, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3901-6790","authenticated-orcid":false,"given":"Zijian","family":"Li","sequence":"additional","affiliation":[{"name":"College of Artificial Intelligence, Dalian Maritime University, Dalian, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4037-3149","authenticated-orcid":false,"given":"Tony Q.S.","family":"Quek","sequence":"additional","affiliation":[{"name":"Singapore University of Technology and Design, Singapore"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/mcom.001.2400685"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TCCN.2025.3601015"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.jii.2024.100694"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/WCNC51071.2022.9771909"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TCOMM.2022.3184160"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2025.3536093"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2025.3580365"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2024.3505155"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2024.3502685"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2025.3579597"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/MCOM.001.2400692"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.5220\/0013228700004558"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2025.3590507"},{"article-title":"From turbulence to tranquility: AI-driven low-altitude network","year":"2025","author":"Tekbyk","key":"ref14"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TNSE.2020.3014385"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TNSE.2023.3282870"},{"article-title":"Stanford Alpaca: An instruction-following LLaMA model (2023)","year":"2023","author":"Taori","key":"ref17"},{"key":"ref18","first-page":"8130","article-title":"Recovering private text in federated learning of language models","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"35","author":"Gupta","year":"2022"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2022.3161132"},{"key":"ref20","first-page":"1273","article-title":"Communication-efficient learning of deep networks from decentralized data","volume-title":"Proc. Artif. Intell. Statist.","author":"McMahan","year":"2017"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TNSE.2024.3410275"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TNSE.2025.3576322"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1145\/3485832.3485837"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2941376"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TNSE.2023.3332642"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/MWC.2025.3597910"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2024.3449129"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/SECON55815.2022.9918588"},{"article-title":"BadNets: Identifying vulnerabilities in the machine learning model supply chain","year":"2017","author":"Gu","key":"ref29"},{"article-title":"Natural backdoor attack on text data","year":"2020","author":"Sun","key":"ref30"},{"issue":"8","key":"ref31","article-title":"Language models are unsupervised multitask learners","volume":"1","author":"Radford","year":"2019","journal-title":"OpenAI Blog"},{"article-title":"TinyLlama: An open-source small language model","year":"2024","author":"Zhang","key":"ref32"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2024.naacl-long.171"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/MNET.2024.3494862"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2025.3570202"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/MWC.007.2400133"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/TC.2023.3272801"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5963"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2025.3633953"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1145\/3664647.3681094"},{"key":"ref41","article-title":"Improving generalization in federated learning with highly heterogeneous data via momentum-based stochastic controlled weight averaging","volume-title":"Proc. 42nd Int. Conf. Mach. Learn.","author":"Liu","year":"2025"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2025.108038"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2024.3427709"},{"article-title":"H-FEDSN: Personalized sparse networks for efficient and accurate hierarchical federated learning for IoT applications","year":"2024","author":"Gao","key":"ref44"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1145\/3716550.3722017"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2022.3232891"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2024.3523947"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2022.3195073"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/MSN60784.2023.00084"},{"article-title":"Agentic satellite-augmented low-altitude economy and terrestrial networks: A survey on generative approaches","year":"2025","author":"Gao","key":"ref50"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/MWC.2025.3603750"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2024.3350886"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/TCCN.2025.3601015"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2025.3565005"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2024.3439696"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2023.3298888"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2023.3239339"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2022.3226867"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/MWC.2025.3603750"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1109\/tccn.2025.3586868"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/pimrc62392.2025.11274957"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2023.3298935"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2024.3523381"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1109\/TCE.2025.3587021"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1162\/coli_a_00426"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.acl-long.37"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.acl-long.725"},{"article-title":"BadGPT: Exploring security vulnerabilities of ChatGPT via backdoor attacks to InstructGPT","year":"2023","author":"Shi","key":"ref68"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2024.findings-acl.468"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2024.findings-naacl.94"},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00409"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1109\/SmartCity64275.2024.00016"},{"key":"ref73","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2020.11.025"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00454"},{"key":"ref75","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-022-03974-7"},{"key":"ref76","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2023.3257878"},{"key":"ref77","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2022.3212733"},{"key":"ref78","first-page":"2938","article-title":"How to backdoor federated learning","volume-title":"Proc. Int. Conf. Artif. Intell. Statist.","author":"Bagdasarian","year":"2020"},{"key":"ref79","first-page":"1605","article-title":"Local model poisoning attacks to $\\lbrace$Byzantine-Robust$\\rbrace$ federated learning","volume-title":"Proc. 29th USENIX Secur. Symp. (USENIX Secur. 20)","author":"Fang","year":"2020"},{"key":"ref80","article-title":"DBA: Distributed backdoor attacks against federated learning","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Xie","year":"2019"},{"article-title":"Vulnerabilities of foundation model integrated federated learning under adversarial threats","year":"2024","author":"Wu","key":"ref81"},{"key":"ref82","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2022.3182979"},{"key":"ref83","article-title":"Backdoor threats from compromised foundation models to federated learning","volume-title":"Proc. Int. Workshop Federated Learn. Age Found. Models Conjunction NeurIPS 2023","author":"Li","year":"2023"},{"key":"ref84","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D13-1170"},{"issue":"12","key":"ref85","article-title":"Twitter sentiment classification using distant supervision","volume":"1","author":"Go","year":"2009","journal-title":"CS224N Project Rep."},{"key":"ref86","first-page":"207","article-title":"Sentiment analysis in amazon reviews using probabilistic machine learning","volume":"42","author":"Rain","year":"2013","journal-title":"Swarthmore College"},{"key":"ref87","first-page":"649","article-title":"Character-level convolutional networks for text classification","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Zhang","year":"2015"},{"key":"ref88","doi-asserted-by":"publisher","DOI":"10.1145\/2488388.2488466"},{"key":"ref89","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/W18-5102"},{"key":"ref90","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/S18-1001"},{"key":"ref91","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1810.04805"},{"article-title":"Roberta: A robustly optimized bert pretraining approach","year":"2019","author":"Liu","key":"ref92"},{"key":"ref93","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.emnlp-main.374"},{"key":"ref94","doi-asserted-by":"publisher","DOI":"10.1109\/EuroSP51992.2021.00022"},{"key":"ref95","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.acl-long.431"},{"key":"ref96","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.emnlp-main.241"},{"key":"ref97","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.naacl-main.165"},{"key":"ref98","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.acl-long.377"},{"key":"ref99","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.acl-main.249"},{"key":"ref100","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.emnlp-main.752"},{"key":"ref101","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2021.04.105"},{"key":"ref102","first-page":"5009","article-title":"A unified evaluation of textual backdoor learning: Frameworks and benchmarks","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"35","author":"Cui","year":"2022"},{"key":"ref103","first-page":"21616","article-title":"Distributed training with heterogeneous data: Bridging median-and mean-based algorithms","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"33","author":"Chen","year":"2020"},{"key":"ref104","first-page":"5650","article-title":"Byzantine-robust distributed learning: Towards optimal statistical rates","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Yin","year":"2018"},{"key":"ref105","first-page":"118","article-title":"Machine learning with adversaries: Byzantine tolerant gradient descent","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Blanchard","year":"2017"},{"key":"ref106","article-title":"The limitations of federated learning in Sybil settings","volume-title":"Proc. 23rd Int. Symp. Res. Attacks, Intrusions Defenses","author":"Fung","year":"2020"},{"article-title":"BERTScore: Evaluating text generation with BERT","year":"2019","author":"Zhang","key":"ref107"},{"key":"ref108","doi-asserted-by":"publisher","DOI":"10.3115\/1073083.1073135"},{"key":"ref109","first-page":"74","article-title":"Rouge: A package for automatic evaluation of summaries","volume-title":"Proc. Text Summarization Branches Out","author":"Lin","year":"2004"},{"key":"ref110","doi-asserted-by":"publisher","DOI":"10.1121\/1.2016299"},{"key":"ref111","first-page":"262","article-title":"Optimizing semantic coherence in topic models","volume-title":"Proc. 2011 Conf. Empirical Methods Natural Lang. Process.","author":"Mimno","year":"2011"},{"key":"ref112","doi-asserted-by":"publisher","DOI":"10.1109\/TG.2020.3020015"},{"key":"ref113","doi-asserted-by":"publisher","DOI":"10.1145\/3359789.3359790"},{"article-title":"GPT-4 Technical Report","year":"2023","author":"Achiam","key":"ref114"},{"article-title":"OpenAI O1 system card","year":"2024","author":"Jaech","key":"ref115"},{"key":"ref116","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-025-09422-z"},{"article-title":"Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context","year":"2024","author":"Team","key":"ref117"}],"container-title":["IEEE Transactions on Network Science and Engineering"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6488902\/11264281\/11219205.pdf?arnumber=11219205","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,26]],"date-time":"2025-12-26T18:25:08Z","timestamp":1766773508000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11219205\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"references-count":117,"URL":"https:\/\/doi.org\/10.1109\/tnse.2025.3626056","relation":{},"ISSN":["2327-4697","2334-329X"],"issn-type":[{"type":"electronic","value":"2327-4697"},{"type":"electronic","value":"2334-329X"}],"subject":[],"published":{"date-parts":[[2026]]}}}