{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,4]],"date-time":"2026-02-04T18:58:06Z","timestamp":1770231486757,"version":"3.49.0"},"reference-count":45,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"1","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"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Dependable and Secure Comput."],"published-print":{"date-parts":[[2026,1]]},"DOI":"10.1109\/tdsc.2025.3605597","type":"journal-article","created":{"date-parts":[[2025,9,3]],"date-time":"2025-09-03T17:55:46Z","timestamp":1756922146000},"page":"343-355","source":"Crossref","is-referenced-by-count":4,"title":["Shortcuts Everywhere and Nowhere: Exploring Multi-Trigger Backdoor Attacks"],"prefix":"10.1109","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5032-8571","authenticated-orcid":false,"given":"Yige","family":"Li","sequence":"first","affiliation":[{"name":"Shanghai Key Laboratory of Intelligent Information, School of CS, Fudan University, Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7440-5567","authenticated-orcid":false,"given":"Jiabo","family":"He","sequence":"additional","affiliation":[{"name":"Bosch Research Asia Pacific &#x0026; Bosch Center for Artificial Intelligence (BCAI), Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2793-6680","authenticated-orcid":false,"given":"Hanxun","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Computing and Information Systems, University of Melbourne, Parkville, VI, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3545-1392","authenticated-orcid":false,"given":"Jun","family":"Sun","sequence":"additional","affiliation":[{"name":"School of Computing and Information Systems, Singapore Management University, Singapore"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2099-4973","authenticated-orcid":false,"given":"Xingjun","family":"Ma","sequence":"additional","affiliation":[{"name":"Shanghai Key Laboratory of Intelligent Information, School of CS, Fudan University, Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1907-8567","authenticated-orcid":false,"given":"Yu-Gang","family":"Jiang","sequence":"additional","affiliation":[{"name":"Shanghai Key Laboratory of Intelligent Information, School of CS, Fudan University, Shanghai, China"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref2","article-title":"An image is worth 16x16 words: Transformers for image recognition at scale","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Dosovitskiy","year":"2021"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1810.04805"},{"key":"ref4","first-page":"1877","article-title":"Language models are few-shot learners","volume-title":"Proc. 34th Int. Conf. Neural Inf. Process. Syst.","author":"Mann"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2016.7472621"},{"key":"ref6","article-title":"BadNets: Identifying vulnerabilities in the machine learning model supply chain","author":"Gu","year":"2017"},{"key":"ref7","article-title":"Targeted backdoor attacks on deep learning systems using data poisoning","author":"Chen","year":"2017"},{"key":"ref8","article-title":"Rethinking the trigger of backdoor attack","author":"Li","year":"2020"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2019.00031"},{"key":"ref10","article-title":"Neural attention distillation: Erasing backdoor triggers from deep neural networks","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Li"},{"key":"ref11","first-page":"16913","article-title":"Adversarial neuron pruning purifies backdoored deep models","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Wu"},{"key":"ref12","first-page":"19837","article-title":"Reconstructive neuron pruning for backdoor defense","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Li"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-00470-5_13"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TDSC.2020.3028448"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-023-05228-6"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/AISP57993.2023.10134794"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2024.3417410"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ICSIP61881.2024.10671403"},{"key":"ref19","first-page":"8011","article-title":"Spectral signatures in backdoor attacks","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Tran"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58607-2_11"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1145\/3372297.3423362"},{"key":"ref22","first-page":"3454","article-title":"Input-aware dynamic backdoor attack","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Nguyen"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i2.16201"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01615"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2022.3182979"},{"key":"ref26","article-title":"Detecting backdoor attacks on deep neural networks by activation clustering","volume-title":"Proc. Conf. Assoc. Adv. Artif. Intell. Workshop","author":"Chen"},{"key":"ref27","article-title":"TABOR: A highly accurate approach to inspecting and restoring trojan backdoors in ai systems","author":"Guo","year":"2019"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/SP40001.2021.00034"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1145\/3359789.3359790"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01616"},{"key":"ref31","article-title":"Distilling cognitive backdoor patterns within an image","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Huang"},{"key":"ref32","first-page":"14900","article-title":"Anti-backdoor learning: Training clean models on poisoned data","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Li"},{"key":"ref33","article-title":"Backdoor defense via decoupling the training process","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Huang"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-20065-6_11"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2024.3436508"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.14722\/ndss.2018.23291"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP.2019.8802997"},{"key":"ref38","article-title":"Clean-label backdoor attacks","author":"Turner","year":"2019"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1145\/3319535.3363216"},{"key":"ref40","article-title":"WaNet\u2013imperceptible warping-based backdoor attack","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Nguyen"},{"key":"ref41","article-title":"MobileNets: Efficient convolutional neural networks for mobile vision applications","author":"Howard","year":"2017"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref43","first-page":"38013","article-title":"UMD: Unsupervised model detection for X2X backdoor attacks","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Xiang"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/SP54263.2024.00015"},{"issue":"11","key":"ref45","first-page":"2579","article-title":"Visualizing data using T-SNE","volume":"9","author":"Van der Maaten","year":"2008","journal-title":"J. Mach. Learn. Res."}],"container-title":["IEEE Transactions on Dependable and Secure Computing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/8858\/11354469\/11150583.pdf?arnumber=11150583","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,20]],"date-time":"2026-01-20T23:23:31Z","timestamp":1768951411000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11150583\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1]]},"references-count":45,"journal-issue":{"issue":"1"},"URL":"https:\/\/doi.org\/10.1109\/tdsc.2025.3605597","relation":{},"ISSN":["1545-5971","1941-0018","2160-9209"],"issn-type":[{"value":"1545-5971","type":"print"},{"value":"1941-0018","type":"electronic"},{"value":"2160-9209","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,1]]}}}