{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,16]],"date-time":"2026-05-16T00:05:07Z","timestamp":1778889907170,"version":"3.51.4"},"reference-count":50,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"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":["61902306"],"award-info":[{"award-number":["61902306"]}],"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":["61632015"],"award-info":[{"award-number":["61632015"]}],"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":["61602369"],"award-info":[{"award-number":["61602369"]}],"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":["U1766215"],"award-info":[{"award-number":["U1766215"]}],"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":["61772408"],"award-info":[{"award-number":["61772408"]}],"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":["61702414"],"award-info":[{"award-number":["61702414"]}],"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":["61833015"],"award-info":[{"award-number":["61833015"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["2019TQ0251"],"award-info":[{"award-number":["2019TQ0251"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["2020M673439"],"award-info":[{"award-number":["2020M673439"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Innovative Research Group of the National Natural Science Foundation of China","award":["61721002"],"award-info":[{"award-number":["61721002"]}]},{"name":"Ministry of Education Innovation Research Team","award":["IRT_17R86"],"award-info":[{"award-number":["IRT_17R86"]}]},{"DOI":"10.13039\/501100016112","name":"Youth Talent Support Plan of Xi\u2019an Association for Science and Technology","doi-asserted-by":"publisher","award":["095920201303"],"award-info":[{"award-number":["095920201303"]}],"id":[{"id":"10.13039\/501100016112","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001381","name":"National Research Foundation, Prime Minister\u2019s Office, Singapore, under its National Cybersecurity Research and Development Program","doi-asserted-by":"publisher","award":["NRF2018NCR-NCR005-0001"],"award-info":[{"award-number":["NRF2018NCR-NCR005-0001"]}],"id":[{"id":"10.13039\/501100001381","id-type":"DOI","asserted-by":"publisher"}]},{"name":"NRF Investigatorship","award":["NRFI06-2020-0022"],"award-info":[{"award-number":["NRFI06-2020-0022"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans.Inform.Forensic Secur."],"published-print":{"date-parts":[[2021]]},"DOI":"10.1109\/tifs.2021.3103064","type":"journal-article","created":{"date-parts":[[2021,8,6]],"date-time":"2021-08-06T20:00:06Z","timestamp":1628280006000},"page":"4117-4132","source":"Crossref","is-referenced-by-count":37,"title":["Text Backdoor Detection Using an Interpretable RNN Abstract Model"],"prefix":"10.1109","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9327-0987","authenticated-orcid":false,"given":"Ming","family":"Fan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4477-9821","authenticated-orcid":false,"given":"Ziliang","family":"Si","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaofei","family":"Xie","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7300-9215","authenticated-orcid":false,"given":"Yang","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7600-0934","authenticated-orcid":false,"given":"Ting","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1016\/0890-5401(87)90052-6"},{"key":"ref38","first-page":"5247","article-title":"Extracting automata from recurrent neural networks using queries and counterexamples","author":"weiss","year":"2018","journal-title":"Proc ICML"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/N16-1174"},{"key":"ref32","first-page":"4765","article-title":"A unified approach to interpreting model predictions","author":"lundberg","year":"2017","journal-title":"Proc NIPS"},{"key":"ref31","year":"2019","journal-title":"Keras 2 3 1"},{"key":"ref30","year":"2020","journal-title":"Ag News Classification Dataset"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.7551\/mitpress\/7443.001.0001"},{"key":"ref36","article-title":"Learning with interpretable structure from gated RNN","author":"hou","year":"2018","journal-title":"arXiv 1810 10708"},{"key":"ref35","first-page":"1527","article-title":"Anchors: High-precision model-agnostic explanations","author":"ribeiro","year":"2018","journal-title":"Proc AAAI"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313545"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.3115\/1219840.1219855"},{"key":"ref27","first-page":"142","article-title":"Learning word vectors for sentiment analysis","author":"maas","year":"2011","journal-title":"Proc ACL"},{"key":"ref29","year":"2018","journal-title":"Toxic comment classification challenge"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref1","year":"2020","journal-title":"Text Analysis API"},{"key":"ref20","article-title":"TABOR: A highly accurate approach to inspecting and restoring trojan backdoors in AI systems","author":"guo","year":"2019","journal-title":"arXiv 1908 01763"},{"key":"ref22","year":"2019","journal-title":"GloVe Global Vectors for Word Representation"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2020.3021924"},{"key":"ref24","article-title":"Towards interpreting recurrent neural networks through probabilistic abstraction","author":"dong","year":"2019","journal-title":"arXiv 1909 10023"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1145\/3338906.3338954"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2002.1017616"},{"key":"ref25","first-page":"8558","article-title":"Learning deterministic weighted automata with queries and counterexamples","author":"weiss","year":"2019","journal-title":"Proc NIPS"},{"key":"ref50","article-title":"ONION: A simple and effective defense against textual backdoor attacks","author":"qi","year":"2020","journal-title":"arXiv 2011 10369"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.282"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2909068"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/QEST.2011.21"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2019.00031"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1145\/3359789.3359790"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-00470-5_13"},{"key":"ref15","article-title":"NeuronInspect: Detecting backdoors in neural networks via output explanations","author":"huang","year":"2019","journal-title":"arXiv 1911 07399"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.14722\/ndss.2018.23291"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ICCD.2017.16"},{"key":"ref18","article-title":"Detecting backdoor attacks on deep neural networks by activation clustering","author":"chen","year":"2018","journal-title":"arXiv 1811 03728"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.14722\/ndss.2019.23415"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/s11633-019-1211-x"},{"key":"ref3","year":"2020","journal-title":"DeepSpeech"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/800"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/3377811.3380368"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2017.49"},{"key":"ref7","article-title":"Feature squeezing: Detecting adversarial examples in deep neural networks","author":"xu","year":"2017","journal-title":"arXiv 1704 01155"},{"key":"ref49","article-title":"SentiNet: Detecting localized universal attacks against deep learning systems","author":"chou","year":"2018","journal-title":"arXiv 1812 00292"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/EuroSP.2016.36"},{"key":"ref46","article-title":"Local rule-based explanations of black box decision systems","author":"guidotti","year":"2018","journal-title":"arXiv 1805 10820"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939778"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/647"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1145\/3243734.3243792"},{"key":"ref42","article-title":"Understanding neural networks through representation erasure","author":"li","year":"2016","journal-title":"arXiv 1612 08220"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.371"},{"key":"ref44","article-title":"Smooth-Grad: Removing noise by adding noise","author":"smilkov","year":"2017","journal-title":"arXiv 1706 03825"},{"key":"ref43","article-title":"Not just a black box: Learning important features through propagating activation differences","author":"shrikumar","year":"2016","journal-title":"arXiv 1605 01713"}],"container-title":["IEEE Transactions on Information Forensics and Security"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10206\/9151439\/09508422.pdf?arnumber=9508422","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T14:52:44Z","timestamp":1652194364000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9508422\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"references-count":50,"URL":"https:\/\/doi.org\/10.1109\/tifs.2021.3103064","relation":{},"ISSN":["1556-6013","1556-6021"],"issn-type":[{"value":"1556-6013","type":"print"},{"value":"1556-6021","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]}}}