{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T14:23:17Z","timestamp":1785421397902,"version":"3.56.0"},"reference-count":52,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2023YFB2704700"],"award-info":[{"award-number":["2023YFB2704700"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62472276"],"award-info":[{"award-number":["62472276"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100010098","name":"Shanghai Committee of Science and Technology, China","doi-asserted-by":"publisher","award":["23511101000"],"award-info":[{"award-number":["23511101000"]}],"id":[{"id":"10.13039\/100010098","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100010098","name":"Shanghai Committee of Science and Technology, China","doi-asserted-by":"publisher","award":["24BC3200400"],"award-info":[{"award-number":["24BC3200400"]}],"id":[{"id":"10.13039\/100010098","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Science and Technology Project of State Grid Corporation of China","award":["5700-202321603A-3-2-ZN"],"award-info":[{"award-number":["5700-202321603A-3-2-ZN"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans.Inform.Forensic Secur."],"published-print":{"date-parts":[[2025]]},"DOI":"10.1109\/tifs.2025.3553803","type":"journal-article","created":{"date-parts":[[2025,3,22]],"date-time":"2025-03-22T00:31:08Z","timestamp":1742603468000},"page":"3601-3615","source":"Crossref","is-referenced-by-count":11,"title":["DDL: Effective and Comprehensible Interpretation Framework for Diverse Deepfake Detectors"],"prefix":"10.1109","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7193-8405","authenticated-orcid":false,"given":"Zekun","family":"Sun","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7673-9843","authenticated-orcid":false,"given":"Na","family":"Ruan","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6831-3973","authenticated-orcid":false,"given":"Jianhua","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","first-page":"6840","article-title":"Denoising diffusion probabilistic models","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"33","author":"Ho"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/3422622"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1312.6114"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2020.06.014"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/PEEIC59336.2023.10450604"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00009"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.02048"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58610-2_6"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00402"},{"issue":"1","key":"ref10","first-page":"1929","article-title":"Dropout: A simple way to prevent neural networks from overfitting","volume":"15","author":"Srivastava","year":"2014","journal-title":"J. Mach. Learn. Res."},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1017\/S0962492921000027"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/N16-3020"},{"key":"ref13","first-page":"4768","article-title":"A unified approach to interpreting model predictions","volume-title":"Proc. Adv. Neural Inf. Process. Syst. (NIPS)","volume":"30","author":"Lundberg"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.371"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.319"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.74"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/WACV.2018.00097"},{"key":"ref18","first-page":"3319","article-title":"Axiomatic attribution for deep networks","volume-title":"Proc. Int. Conf. Mach. Learn.","volume":"70","author":"Sundararajan"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00505"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.195"},{"key":"ref21","article-title":"Exposing DeepFake videos by detecting face warping artifacts","author":"Li","year":"2018","journal-title":"arXiv:1811.00656"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW56347.2022.00011"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00505"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.2983686"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2022.3141262"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2022.3233774"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00083"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.502"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-06365-7_22"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1145\/3464307"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW53098.2021.00103"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN48605.2020.9207034"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/HPCC-DSS-SmartCity-DependSys53884.2021.00129"},{"key":"ref35","article-title":"Mitigating adversarial attacks in deepfake detection: An exploration of perturbation and AI techniques","author":"Dhesi","year":"2023","journal-title":"arXiv:2302.11704"},{"key":"ref36","article-title":"XAI-based detection of adversarial attacks on deepfake detectors","author":"Pinhasov","year":"2024","journal-title":"arXiv:2403.02955"},{"key":"ref37","article-title":"RISE: Randomized input sampling for explanation of black-box models","author":"Petsiuk","year":"2018","journal-title":"arXiv:1806.07421"},{"key":"ref38","volume-title":"Deepfakes Github","year":"2021"},{"key":"ref39","volume-title":"Face Parsing","year":"2020"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-021-01515-2"},{"issue":"1","key":"ref41","doi-asserted-by":"crossref","DOI":"10.23915\/distill.00022","article-title":"Visualizing the impact of feature attribution baselines","volume":"5","author":"Sturmfels","year":"2020","journal-title":"Distill"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2012.120"},{"key":"ref43","volume-title":"Faceswap Github","year":"2021"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.262"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1145\/3306346.3323035"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00327"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00296"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.00858"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01605"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.02071"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00986"},{"key":"ref52","first-page":"4534","article-title":"DeepfakeBench: A comprehensive benchmark of deepfake detection","volume-title":"Proc. Adv. Neural Inf. Process. Syst. (NIPS)","volume":"36","author":"Yan"}],"container-title":["IEEE Transactions on Information Forensics and Security"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/10206\/10810755\/10937201.pdf?arnumber=10937201","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,4]],"date-time":"2025-04-04T18:36:53Z","timestamp":1743791813000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10937201\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":52,"URL":"https:\/\/doi.org\/10.1109\/tifs.2025.3553803","relation":{},"ISSN":["1556-6013","1556-6021"],"issn-type":[{"value":"1556-6013","type":"print"},{"value":"1556-6021","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]}}}