{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T11:35:33Z","timestamp":1742988933943,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":21,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819610709"},{"type":"electronic","value":"9789819610716"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-981-96-1071-6_18","type":"book-chapter","created":{"date-parts":[[2025,2,7]],"date-time":"2025-02-07T04:04:38Z","timestamp":1738901078000},"page":"197-206","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Universal Face Manipulation Proactive Defense by\u00a0Frequency-Driven Imperceptible Adversarial Attack"],"prefix":"10.1007","author":[{"given":"Jinchang","family":"Wen","sequence":"first","affiliation":[]},{"given":"Jian","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Yunlian","family":"Sun","sequence":"additional","affiliation":[]},{"given":"Massimo","family":"Tistarelli","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,2,8]]},"reference":[{"key":"18_CR1","doi-asserted-by":"publisher","first-page":"2960","DOI":"10.1109\/TIFS.2020.2980792","volume":"15","author":"Y Sun","year":"2020","unstructured":"Sun, Y., Tang, J., Sun, Z., Tistarelli, M.: Facial age and expression synthesis using ordinal ranking adversarial networks. IEEE Trans. Inf. Forensics Secur. 15, 2960\u20132972 (2020)","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"18_CR2","doi-asserted-by":"publisher","first-page":"2679","DOI":"10.1109\/TIFS.2020.2975921","volume":"15","author":"Y Sun","year":"2020","unstructured":"Sun, Y., Tang, J., Shu, X., Sun, Z., Tistarelli, M.: Facial age synthesis with label distribution-guided generative adversarial network. IEEE Trans. Inf. Forensics Secur. 15, 2679\u20132691 (2020)","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"18_CR3","doi-asserted-by":"publisher","first-page":"2425","DOI":"10.1109\/TIFS.2022.3186803","volume":"17","author":"J Wang","year":"2022","unstructured":"Wang, J., Sun, Y., Tang, J.: Lisiam: Localization invariance siamese network for deepfake detection. IEEE Trans. Inf. Forensics Secur. 17, 2425\u20132436 (2022)","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"18_CR4","doi-asserted-by":"crossref","unstructured":"N.\u00a0Ruiz, S.\u00a0A. Bargal, and S.\u00a0Sclaroff, \u201cDisrupting deepfakes: Adversarial attacks against conditional image translation networks and facial manipulation systems,\u201d in ECCV, 2020","DOI":"10.1007\/978-3-030-66823-5_14"},{"key":"18_CR5","unstructured":"L.\u00a0Tang, D.\u00a0Ye, Z.\u00a0Lu, Y.\u00a0Zhang, S.\u00a0Hu, Y.\u00a0Xu, and C.\u00a0Chen, \u201cFeature extraction matters more: Universal deepfake disruption through attacking ensemble feature extractors,\u201d arXiv preprint arXiv:2303.00200"},{"key":"18_CR6","doi-asserted-by":"crossref","unstructured":"H.\u00a0Huang, Y.\u00a0Wang, Z.\u00a0Chen, Y.\u00a0Zhang, Y.\u00a0Li, Z.\u00a0Tang, W.\u00a0Chu, J.\u00a0Chen, W.\u00a0Lin, and K.-K. Ma, \u201cCmua-watermark: A cross-model universal adversarial watermark for combating deepfakes,\u201d in AAAI, 2022","DOI":"10.1609\/aaai.v36i1.19982"},{"key":"18_CR7","doi-asserted-by":"crossref","unstructured":"Q. Huang, J. Zhang, W. Zhou, W. Zhang, and N. Yu, Initiative defense against facial manipulation,\u201d in AAAI, 2021","DOI":"10.1609\/aaai.v35i2.16254"},{"key":"18_CR8","doi-asserted-by":"crossref","unstructured":"C. Xiao, B. Li, J.-Y. Zhu, W. He, M. Liu, and D. Song, Generating adversarial examples with adversarial networks,\u201d arXiv preprint arXiv:1801.02610, 2018","DOI":"10.24963\/ijcai.2018\/543"},{"key":"18_CR9","doi-asserted-by":"crossref","unstructured":"H.\u00a0Zhang, D.\u00a0Chen, and C.\u00a0Wang, \u201cConfidence-aware multi-teacher knowledge distillation,\u201d in ICASSP, pp.\u00a04498\u20134502, IEEE, 2022","DOI":"10.1109\/ICASSP43922.2022.9747534"},{"key":"18_CR10","doi-asserted-by":"crossref","unstructured":"C.\u00a0Luo, Q.\u00a0Lin, W.\u00a0Xie, B.\u00a0Wu, J.\u00a0Xie, and L.\u00a0Shen, \u201cFrequency-driven imperceptible adversarial attack on semantic similarity,\u201d in CVPR, 2022","DOI":"10.1109\/CVPR52688.2022.01488"},{"key":"18_CR11","unstructured":"T.\u00a0Zheng and W.\u00a0Deng, \u201cCross-pose lfw: A database for studying cross-pose face recognition in unconstrained environments,\u201d Beijing University of Posts and Telecommunications, Tech. Rep, vol.\u00a05, no.\u00a07, 2018"},{"issue":"8","key":"18_CR12","doi-asserted-by":"publisher","first-page":"1377","DOI":"10.1080\/02699930903485076","volume":"24","author":"O Langner","year":"2010","unstructured":"Langner, O., Dotsch, R., Bijlstra, G., Wigboldus, D.H., Hawk, S.T., Van Knippenberg, A.: Presentation and validation of the radboud faces database. Cogn. Emot. 24(8), 1377\u20131388 (2010)","journal-title":"Cogn. Emot."},{"key":"18_CR13","doi-asserted-by":"crossref","unstructured":"Y.\u00a0Choi, M.\u00a0Choi, M.\u00a0Kim, J.-W. Ha, S.\u00a0Kim, and J.\u00a0Choo, \u201cStargan: Unified generative adversarial networks for multi-domain image-to-image translation,\u201d in CVPR, 2018","DOI":"10.1109\/CVPR.2018.00916"},{"key":"18_CR14","doi-asserted-by":"crossref","unstructured":"H.\u00a0Tang, D.\u00a0Xu, N.\u00a0Sebe, and Y.\u00a0Yan, \u201cAttention-guided generative adversarial networks for unsupervised image-to-image translation,\u201d in IJCNN, 2019","DOI":"10.1109\/IJCNN.2019.8851881"},{"issue":"11","key":"18_CR15","doi-asserted-by":"publisher","first-page":"5464","DOI":"10.1109\/TIP.2019.2916751","volume":"28","author":"Z He","year":"2019","unstructured":"He, Z., Zuo, W., Kan, M., Shan, S., Chen, X.: Attgan: Facial attribute editing by only changing what you want. IEEE Trans. Image Process. 28(11), 5464\u20135478 (2019)","journal-title":"IEEE Trans. Image Process."},{"key":"18_CR16","doi-asserted-by":"crossref","unstructured":"X.\u00a0Li, S.\u00a0Zhang, J.\u00a0Hu, L.\u00a0Cao, X.\u00a0Hong, X.\u00a0Mao, F.\u00a0Huang, Y.\u00a0Wu, and R.\u00a0Ji, \u201cImage-to-image translation via hierarchical style disentanglement,\u201d in CVPR, 2021","DOI":"10.1109\/CVPR46437.2021.00853"},{"key":"18_CR17","doi-asserted-by":"crossref","unstructured":"A.\u00a0Kurakin, I.\u00a0J. Goodfellow, and S.\u00a0Bengio, \u201cAdversarial examples in the physical world,\u201d in Artificial intelligence safety and security, pp.\u00a099\u2013112, Chapman and Hall\/CRC, 2018","DOI":"10.1201\/9781351251389-8"},{"key":"18_CR18","doi-asserted-by":"crossref","unstructured":"Y.\u00a0Dong, F.\u00a0Liao, T.\u00a0Pang, H.\u00a0Su, J.\u00a0Zhu, X.\u00a0Hu, and J.\u00a0Li, \u201cBoosting adversarial attacks with momentum,\u201d in CVPR, 2018","DOI":"10.1109\/CVPR.2018.00957"},{"key":"18_CR19","unstructured":"A.\u00a0Madry, A.\u00a0Makelov, L.\u00a0Schmidt, D.\u00a0Tsipras, and A.\u00a0Vladu, \u201cTowards deep learning models resistant to adversarial attacks,\u201d arXiv preprint arXiv:1706.06083, 2017"},{"key":"18_CR20","doi-asserted-by":"crossref","unstructured":"C.\u00a0Xie, Z.\u00a0Zhang, Y.\u00a0Zhou, S.\u00a0Bai, J.\u00a0Wang, Z.\u00a0Ren, and A.\u00a0L. Yuille, \u201cImproving transferability of adversarial examples with input diversity,\u201d in CVPR, 2019","DOI":"10.1109\/CVPR.2019.00284"},{"key":"18_CR21","unstructured":"F.\u00a0Croce and M.\u00a0Hein, \u201cReliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks,\u201d in ICML, 2020"}],"container-title":["Lecture Notes in Computer Science","Biometric Recognition"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-96-1071-6_18","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,2,7]],"date-time":"2025-02-07T04:04:51Z","timestamp":1738901091000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-96-1071-6_18"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9789819610709","9789819610716"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-981-96-1071-6_18","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"8 February 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CCBR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Chinese Conference on Biometric Recognition","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Nanjing","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 November 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24 November 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ccbr2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ccbr99.cn\/index.html","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}