{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,22]],"date-time":"2026-07-22T16:39:02Z","timestamp":1784738342634,"version":"3.55.0"},"reference-count":47,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"9","license":[{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"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":["U2436208"],"award-info":[{"award-number":["U2436208"]}],"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":["62372129"],"award-info":[{"award-number":["62372129"]}],"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":["62372126"],"award-info":[{"award-number":["62372126"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Guangdong S&T Program","award":["2024B0101010002"],"award-info":[{"award-number":["2024B0101010002"]}]},{"name":"Project of Guangdong Key Laboratory of Industrial Control System Security","award":["2024B1212020010"],"award-info":[{"award-number":["2024B1212020010"]}]},{"DOI":"10.13039\/501100021171","name":"Basic and Applied Basic Research Foundation of Guangdong Province","doi-asserted-by":"publisher","award":["2023A1515030142"],"award-info":[{"award-number":["2023A1515030142"]}],"id":[{"id":"10.13039\/501100021171","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Strategic Research and Consulting Project of Chinese Academy of Engineering","award":["2023-JB-13"],"award-info":[{"award-number":["2023-JB-13"]}]},{"name":"Guangzhou Basic and Applied Basic Research Foundation","award":["2025A04J2947"],"award-info":[{"award-number":["2025A04J2947"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Neural Netw. Learning Syst."],"published-print":{"date-parts":[[2025,9]]},"DOI":"10.1109\/tnnls.2025.3554217","type":"journal-article","created":{"date-parts":[[2025,4,22]],"date-time":"2025-04-22T13:41:51Z","timestamp":1745329311000},"page":"16186-16197","source":"Crossref","is-referenced-by-count":7,"title":["Neural Honeypoint: An Active Defense Framework Against Model Inversion Attacks"],"prefix":"10.1109","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9791-0980","authenticated-orcid":false,"given":"Yixiao","family":"Xu","sequence":"first","affiliation":[{"name":"School of Cyberspace Security, Beijing University of Posts and Telecommunications, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2290-046X","authenticated-orcid":false,"given":"Mohan","family":"Li","sequence":"additional","affiliation":[{"name":"Cyberspace Institute of Advanced Technology, Guangdong Key Laboratory of Industrial Control System Security and Huangpu Research School, Guangzhou University, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Binxing","family":"Fang","sequence":"additional","affiliation":[{"name":"Cyberspace Institute of Advanced Technology, Guangdong Key Laboratory of Industrial Control System Security and Huangpu Research School, Guangzhou University, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0246-0778","authenticated-orcid":false,"given":"Yuan","family":"Liu","sequence":"additional","affiliation":[{"name":"Cyberspace Institute of Advanced Technology, Guangdong Key Laboratory of Industrial Control System Security and Huangpu Research School, Guangzhou University, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9409-5359","authenticated-orcid":false,"given":"Zhihong","family":"Tian","sequence":"additional","affiliation":[{"name":"Cyberspace Institute of Advanced Technology, Guangdong Key Laboratory of Industrial Control System Security and Huangpu Research School, Guangzhou University, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2023.3284666"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2023.3262277"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2016.2598616"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2023.3254579"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TCSS.2022.3179659"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2022.3175719"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TSUSC.2023.3240411"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2022.3142820"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2022.3172986"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TDSC.2023.3306748"},{"key":"ref11","first-page":"1433","article-title":"Mitigating membership inference attacks by self-distillation through a novel ensemble architecture","volume-title":"Proc. 31st USENIX Security Symp. (USENIX Security)","author":"Tang"},{"key":"ref12","first-page":"2671","article-title":"A data-free backdoor injection approach in neural networks","volume-title":"Proc. 32nd USENIX Secur. Symp. (USENIX Secur.)","author":"Lv"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1145\/2810103.2813677"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00033"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01587"},{"key":"ref16","first-page":"9706","article-title":"Variational model inversion attacks","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"34","author":"Wang"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.14722\/ndss.2022.24335"},{"key":"ref18","first-page":"20522","article-title":"Plug & play attacks: Towards robust and flexible model inversion attacks","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Struppek"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i13.17387"},{"key":"ref20","article-title":"Defending model inversion and membership inference attacks via prediction purification","author":"Yang","year":"2020","journal-title":"arXiv:2005.03915"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2023.3295944"},{"key":"ref22","first-page":"3353","article-title":"Adversarial training for free","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"32","author":"Shafahi"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00401"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2019.2962914"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.15302\/j-sscae-2023.06.007"},{"key":"ref26","first-page":"214","article-title":"Wasserstein generative adversarial networks","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Arjovsky"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00813"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1145\/3319535.3354261"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP49357.2023.10095514"},{"issue":"1","key":"ref30","first-page":"949","article-title":"Natural evolution strategies","volume":"15","author":"Wierstra","year":"2014","journal-title":"J. Mach. Learn. Res."},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2022.3207915"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1145\/2976749.2978318"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CSR51186.2021.9527945"},{"issue":"5","key":"ref34","first-page":"1230","article-title":"Development of deception defense technology and exploration of its large language model applications","volume":"61","author":"Wang","year":"2024","journal-title":"Comput. Res. Develop."},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2020.3044576"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i17.17786"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2024.3455564"},{"key":"ref38","first-page":"41429","article-title":"Detecting adversarial data by probing multiple perturbations using expected perturbation score","volume-title":"Proc. Int. Conf. Mach. Learn. (ICML)","volume":"202","author":"Zhang"},{"key":"ref39","first-page":"1685","article-title":"Towards a proactive ML approach for detecting backdoor poison samples","volume-title":"Proc. 32nd USENIX Secur. Symp. (USENIX Secur.)","author":"Qi"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2022.3167482"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP.2014.7025068"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.425"},{"key":"ref43","first-page":"2","article-title":"Novel dataset for fine-grained image categorization","volume-title":"Proc. 1st Workshop Fine-Grained Vis. Categorization","author":"Khosla"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW56347.2022.00309"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.308"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.2970919"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00821"}],"container-title":["IEEE Transactions on Neural Networks and Learning Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/5962385\/11151745\/10973310.pdf?arnumber=10973310","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,8]],"date-time":"2025-09-08T17:47:05Z","timestamp":1757353625000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10973310\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9]]},"references-count":47,"journal-issue":{"issue":"9"},"URL":"https:\/\/doi.org\/10.1109\/tnnls.2025.3554217","relation":{},"ISSN":["2162-237X","2162-2388"],"issn-type":[{"value":"2162-237X","type":"print"},{"value":"2162-2388","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,9]]}}}