{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,12]],"date-time":"2026-09-12T08:07:02Z","timestamp":1789200422418,"version":"build-2803163510"},"reference-count":36,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/100012906","name":"Shandong Provincial Education Department","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100012906","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002767","name":"Hunan Provincial Science and Technology Department","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100002767","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Applied Soft Computing"],"published-print":{"date-parts":[[2026,11]]},"DOI":"10.1016\/j.asoc.2026.116172","type":"journal-article","created":{"date-parts":[[2026,8,6]],"date-time":"2026-08-06T16:34:09Z","timestamp":1786034049000},"page":"116172","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"PC","title":["FBBA: Feature-isolation-based full-target black-box backdoor attacks"],"prefix":"10.1016","volume":"203","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-9517-2667","authenticated-orcid":false,"given":"Yangxu","family":"Yin","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5343-1440","authenticated-orcid":false,"given":"Honglong","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1931-9655","authenticated-orcid":false,"given":"Huansheng","family":"Xue","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kai","family":"Lin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peng","family":"Sun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5160-5999","authenticated-orcid":false,"given":"Liantao","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weifeng","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.asoc.2026.116172_bib0005","series-title":"Proceedings of the International Conference on Learning Representations","article-title":"Targeted attack against deep neural networks via flipping limited weight bits","author":"Bai","year":"2021"},{"key":"10.1016\/j.asoc.2026.116172_bib0010","doi-asserted-by":"crossref","DOI":"10.1109\/HPCC-DSS-SmartCity-DependSys57074.2022.00131","article-title":"LightSCA: lightweight side-channel attack via discrete cosine transform and residual networks","author":"Cai","year":"2022"},{"key":"10.1016\/j.asoc.2026.116172_bib0015","author":"Chen"},{"key":"10.1016\/j.asoc.2026.116172_bib0020","series-title":"Proceedings of the International Joint Conference on Artificial Intelligence","article-title":"DeepInspect: a black-box trojan detection and mitigation framework for deep neural networks","author":"Chen","year":"2019"},{"key":"10.1016\/j.asoc.2026.116172_bib0025","doi-asserted-by":"crossref","first-page":"6923","DOI":"10.1109\/TIFS.2024.3427432","article-title":"Investigating the backdoor on DNNs based on recolorization and reconstruction: from a multi-channel perspective","volume":"19","author":"Chen","year":"2024","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"10.1016\/j.asoc.2026.116172_bib0030","author":"Chen"},{"key":"10.1016\/j.asoc.2026.116172_bib0035","series-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","article-title":"LIRA: learnable, imperceptible and robust backdoor attacks","author":"Doan","year":"2021"},{"key":"10.1016\/j.asoc.2026.116172_bib0040","series-title":"Advances in Neural Information Processing Systems","first-page":"38260","article-title":"Marksman backdoor: backdoor attacks with arbitrary target class","volume":"vol. 35","author":"Doan","year":"2022"},{"key":"10.1016\/j.asoc.2026.116172_bib0045","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","article-title":"FIBA: frequency-injection based backdoor attack in medical image analysis","author":"Feng","year":"2022"},{"issue":"6","key":"10.1016\/j.asoc.2026.116172_bib0050","doi-asserted-by":"crossref","first-page":"7746","DOI":"10.1109\/TDSC.2025.3600427","article-title":"A triple stealthy backdoor: hidden in spatial, frequency, and feature domains","volume":"22","author":"Gao","year":"2025","journal-title":"IEEE Trans. Dependable Secure Comput."},{"key":"10.1016\/j.asoc.2026.116172_bib0055","series-title":"Proceedings of the International Conference on Machine Learning","article-title":"Energy-based backdoor defense without task-specific samples and model retraining","author":"Gao","year":"2024"},{"key":"10.1016\/j.asoc.2026.116172_bib0060","series-title":"Proceedings of the Annual Computer Security Applications Conference","article-title":"STRIP: a defence against trojan attacks on deep neural networks","author":"Gao","year":"2019"},{"key":"10.1016\/j.asoc.2026.116172_bib0065","doi-asserted-by":"crossref","first-page":"47230","DOI":"10.1109\/ACCESS.2019.2909068","article-title":"BadNets: evaluating backdooring attacks on deep neural networks","volume":"7","author":"Gu","year":"2019","journal-title":"IEEE Access"},{"key":"10.1016\/j.asoc.2026.116172_bib0070","doi-asserted-by":"crossref","first-page":"7106","DOI":"10.1109\/TIFS.2025.3581026","article-title":"Silent penetrator: breaching cross-domain federated fine-tuning via feature shift-induced backdoor","volume":"20","author":"Huang","year":"2025","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"issue":"2","key":"10.1016\/j.asoc.2026.116172_bib0075","doi-asserted-by":"crossref","first-page":"1260","DOI":"10.1109\/TII.2022.3173996","article-title":"Multitentacle federated learning over software-defined industrial internet of things against adaptive poisoning attacks","volume":"19","author":"Li","year":"2022","journal-title":"IEEE Trans. Ind. Inform."},{"key":"10.1016\/j.asoc.2026.116172_bib0080","series-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","article-title":"Invisible backdoor attack with sample-specific triggers","author":"Li","year":"2021"},{"key":"10.1016\/j.asoc.2026.116172_bib0085","series-title":"Proceedings of the International Symposium on Research in Attacks, Intrusions, and Defenses","article-title":"Fine-pruning: defending against backdooring attacks on deep neural networks","author":"Liu","year":"2018"},{"key":"10.1016\/j.asoc.2026.116172_bib0090","series-title":"Proceedings of the Annual Network and Distributed System Security Symposium","article-title":"Trojaning attack on neural networks","author":"Liu","year":"2018"},{"key":"10.1016\/j.asoc.2026.116172_bib0095","series-title":"Proceedings of the European Conference on Computer Vision","article-title":"Reflection backdoor: a natural backdoor attack on deep neural networks","author":"Liu","year":"2020"},{"key":"10.1016\/j.asoc.2026.116172_bib0100","series-title":"Proceedings of the International Symposium on Quality Electronic Design","article-title":"A survey on neural trojans","author":"Liu","year":"2020"},{"key":"10.1016\/j.asoc.2026.116172_bib0105","series-title":"Proceedings of the International Conference on Learning Representations","article-title":"WaNet - imperceptible warping-based backdoor attack","author":"Nguyen","year":"2021"},{"key":"10.1016\/j.asoc.2026.116172_bib0110","series-title":"Proceedings of the International Conference on Learning Representations","article-title":"Universal backdoor attacks","author":"Schneider","year":"2024"},{"key":"10.1016\/j.asoc.2026.116172_bib0115","series-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","article-title":"Grad-CAM: visual explanations from deep networks via gradient-based localization","author":"Selvaraju","year":"2017"},{"key":"10.1016\/j.asoc.2026.116172_bib0120","series-title":"Proceedings of the IEEE Symposium on Security and Privacy","article-title":"Neural cleanse: identifying and mitigating backdoor attacks in neural networks","author":"Wang","year":"2019"},{"key":"10.1016\/j.asoc.2026.116172_bib0125","series-title":"Proceedings of the European Conference on Computer Vision","article-title":"An invisible black-box backdoor attack through frequency domain","author":"Wang","year":"2022"},{"issue":"3","key":"10.1016\/j.asoc.2026.116172_bib0130","doi-asserted-by":"crossref","first-page":"1562","DOI":"10.1109\/TDSC.2020.3028448","article-title":"One-to-N & N-to-one: two advanced backdoor attacks against deep learning models","volume":"19","author":"Xue","year":"2020","journal-title":"IEEE Trans. Dependable Secure Comput."},{"key":"10.1016\/j.asoc.2026.116172_bib0135","series-title":"Imperceptible and Multi-Channel Backdoor Attack","author":"Xue","year":"2024"},{"key":"10.1016\/j.asoc.2026.116172_bib0140","series-title":"Compression-Resistant Backdoor Attack Against Deep Neural Networks","author":"Xue","year":"2023"},{"key":"10.1016\/j.asoc.2026.116172_bib0145","doi-asserted-by":"crossref","first-page":"1051","DOI":"10.1109\/OJVT.2025.3550411","article-title":"Exploring graph neural backdoors in vehicular networks: fundamentals, methodologies, applications, and future perspectives","volume":"6","author":"Yang","year":"2025","journal-title":"IEEE Open J. Veh. Technol."},{"key":"10.1016\/j.asoc.2026.116172_bib0150","author":"Yin"},{"key":"10.1016\/j.asoc.2026.116172_bib0155","series-title":"Proceedings of the 33rd ACM International Conference on Multimedia","article-title":"FFCBA: feature-based full-target clean-label backdoor attacks","author":"Yin","year":"2025"},{"key":"10.1016\/j.asoc.2026.116172_bib0160","series-title":"Proceedings of the European Conference on Computer Vision","article-title":"Visualizing and understanding convolutional networks","author":"Zeiler","year":"2014"},{"key":"10.1016\/j.asoc.2026.116172_bib0165","series-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","article-title":"Rethinking the backdoor attacks\u2019 triggers: a frequency perspective","author":"Zeng","year":"2021"},{"issue":"22","key":"10.1016\/j.asoc.2026.116172_bib0170","doi-asserted-by":"crossref","first-page":"22184","DOI":"10.1109\/JIOT.2021.3103138","article-title":"AntiConcealer: reliable detection of adversary concealed behaviors in EdgeAI-assisted IoT","volume":"9","author":"Zhang","year":"2021","journal-title":"IEEE Internet Things J."},{"key":"10.1016\/j.asoc.2026.116172_bib0175","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","article-title":"Backdoor defense via deconfounded representation learning","author":"Zhang","year":"2023"},{"key":"10.1016\/j.asoc.2026.116172_bib0180","series-title":"DMC-Watermark: A Backdoor Richer Watermark for Dual Identity Verification by Dynamic Mask Covering","author":"Zhu","year":"2025"}],"container-title":["Applied Soft Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1568494626016200?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1568494626016200?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,9,12]],"date-time":"2026-09-12T07:54:34Z","timestamp":1789199674000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1568494626016200"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,11]]},"references-count":36,"alternative-id":["S1568494626016200"],"URL":"https:\/\/doi.org\/10.1016\/j.asoc.2026.116172","relation":{},"ISSN":["1568-4946"],"issn-type":[{"value":"1568-4946","type":"print"}],"subject":[],"published":{"date-parts":[[2026,11]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"FBBA: Feature-isolation-based full-target black-box backdoor attacks","name":"articletitle","label":"Article Title"},{"value":"Applied Soft Computing","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.asoc.2026.116172","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"116172"}}