{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,2]],"date-time":"2026-08-02T05:47:11Z","timestamp":1785649631004,"version":"3.56.0"},"publisher-location":"Cham","reference-count":46,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032319296","type":"print"},{"value":"9783032319302","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,8,3]],"date-time":"2026-08-03T00:00:00Z","timestamp":1785715200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,8,3]],"date-time":"2026-08-03T00:00:00Z","timestamp":1785715200000},"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":[[2027]]},"DOI":"10.1007\/978-3-032-31930-2_17","type":"book-chapter","created":{"date-parts":[[2026,8,2]],"date-time":"2026-08-02T05:41:53Z","timestamp":1785649313000},"page":"247-261","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Evaluating Machine Unlearning in\u00a0Fingerphoto Presentation Attack Detection"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9784-1476","authenticated-orcid":false,"given":"Anudeep","family":"Vurity","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6722-5517","authenticated-orcid":false,"given":"Zhisheng","family":"Yan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2675-5810","authenticated-orcid":false,"given":"Massimiliano","family":"Albanese","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,8,3]]},"reference":[{"key":"17_CR1","unstructured":"ISO\/IEC 30107-3: Information technology \u2013 biometric presentation attack detection \u2013 part 3: Testing and reporting (2017)"},{"key":"17_CR2","unstructured":"An Overview of Mobile Biometrics: Techniques and Applications \u2014 aratek.co (2023). https:\/\/www.aratek.co\/news\/an-overview-of-mobile-biometrics-techniques-and-applications"},{"key":"17_CR3","doi-asserted-by":"crossref","unstructured":"Adami, B., Karimian, N.: Contactless fingerprint biometric anti-spoofing: An unsupervised deep learning approach, arXiv preprint arXiv:2311.04148 (2023)","DOI":"10.1109\/IJCB62174.2024.10744434"},{"key":"17_CR4","unstructured":"Becker, A., Liebig, T.: Evaluating machine unlearning via epistemic uncertainty, arXiv preprint arXiv:2208.10836 (2022)"},{"key":"17_CR5","doi-asserted-by":"publisher","unstructured":"Bonato, J., Cotogni, M., Sabetta, L.: Is retain set all you need in machine unlearning? restoring performance of unlearned models with out-of-distribution images. In: European Conference on Computer Vision, pp. 1\u201319. Springer (2024). https:\/\/doi.org\/10.1007\/978-3-031-73232-4_1","DOI":"10.1007\/978-3-031-73232-4_1"},{"key":"17_CR6","doi-asserted-by":"crossref","unstructured":"Bourtoule, L., et al.: Machine unlearning. In: 2021 IEEE Symposium on Security and Privacy (SP), pp. 141\u2013159. IEEE (2021)","DOI":"10.1109\/SP40001.2021.00019"},{"key":"17_CR7","doi-asserted-by":"crossref","unstructured":"Cao, Y., Yang, J.: Towards making systems forget with machine unlearning. In: IEEE Symposium on Security and Privacy, pp. 463\u2013480. IEEE (2015)","DOI":"10.1109\/SP.2015.35"},{"key":"17_CR8","doi-asserted-by":"crossref","unstructured":"Cha, S., Cho, S., Hwang, D., Lee, H., Moon, T., Lee, M.: Learning to unlearn: instance-wise unlearning for pre-trained classifiers. In: Proceedings of the AAAI conference on artificial intelligence, vol.\u00a038, pp. 11186\u201311194 (2024)","DOI":"10.1609\/aaai.v38i10.28996"},{"key":"17_CR9","doi-asserted-by":"crossref","unstructured":"Chen, M., Gao, W., Liu, G., Peng, K., Wang, C.: Boundary unlearning: rapid forgetting of deep networks via shifting the decision boundary. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 7766\u20137775 (2023)","DOI":"10.1109\/CVPR52729.2023.00750"},{"key":"17_CR10","doi-asserted-by":"crossref","unstructured":"Chen, S., Kahla, M., Jia, R., Qi, G.J.: Knowledge-enriched distributional model inversion attacks. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV), pp. 16178\u201316187 (2021)","DOI":"10.1109\/ICCV48922.2021.01587"},{"key":"17_CR11","doi-asserted-by":"crossref","unstructured":"Chundawat, V.S., Tarun, A.K., Mandal, M., Kankanhalli, M.: Can bad teaching induce forgetting? unlearning in deep networks using an incompetent teacher. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 37, pp. 7210\u20137217 (2023)","DOI":"10.1609\/aaai.v37i6.25879"},{"key":"17_CR12","unstructured":"Cotogni, M., Bonato, J., Sabetta, L., Pelosin, F., Nicolosi, A.: Duck: distance-based unlearning via centroid kinematics, arXiv preprint arXiv:2312.02052 (2023)"},{"key":"17_CR13","unstructured":"Dosovitskiy, A., Beyer, L., Kolesnikov, A.: An image is worth 16x16 words: transformers for image recognition at scale. International Conference on Learning Representations (ICLR) (2021)"},{"key":"17_CR14","unstructured":"Fan, C., Liu, J., Zhang, Y., Wong, E., Wei, D., Liu, S.: Salun: Empowering machine unlearning via gradient-based weight saliency in both image classification and generation. arXiv preprint arXiv:2310.12508 (2023)"},{"issue":"7","key":"17_CR15","first-page":"57","volume":"4","author":"D Gentles","year":"2012","unstructured":"Gentles, D., Sankaranarayanan, S.: Application of biometrics in mobile voting. Inter. J. Comput. Netw. Inform. Sec. 4(7), 57 (2012)","journal-title":"Inter. J. Comput. Netw. Inform. Sec."},{"key":"17_CR16","doi-asserted-by":"crossref","unstructured":"Golatkar, A., Achille, A., Soatto, S.: Eternal sunshine of the spotless net: selective forgetting in deep networks. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 9304\u20139312 (2020)","DOI":"10.1109\/CVPR42600.2020.00932"},{"key":"17_CR17","unstructured":"Government of Canada: Personal Information Protection and Electronic Documents Act (PIPEDA) (2025). https:\/\/laws-lois.justice.gc.ca\/eng\/acts\/p-8.6\/, Accessed 20 March 2025"},{"key":"17_CR18","doi-asserted-by":"publisher","first-page":"196","DOI":"10.1109\/TIFS.2021.3134867","volume":"17","author":"SA Grosz","year":"2021","unstructured":"Grosz, S.A., Engelsma, J.J., Liu, E., Jain, A.K.: C2cl: Contact to contactless fingerprint matching. IEEE Trans. Inf. Forensics Secur. 17, 196\u2013210 (2021)","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"17_CR19","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"17_CR20","unstructured":"Heusel, M., Ramsauer, H., Unterthiner, T., Nessler, B., Hochreiter, S.: Gans trained by a two time-scale update rule converge to a local nash equilibrium. In: Advances in Neural Information Processing Systems (NeurIPS) (2017)"},{"key":"17_CR21","doi-asserted-by":"publisher","first-page":"51584","DOI":"10.52202\/075280-2246","volume":"36","author":"J Jia","year":"2023","unstructured":"Jia, J., Liu, J., Ram, P., Yao, Y., Liu, G., Liu, Y., Sharma, P., Liu, S.: Model sparsity can simplify machine unlearning. Adv. Neural. Inf. Process. Syst. 36, 51584\u201351605 (2023)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"17_CR22","unstructured":"Kannala, J., Rahtu, E.: Bsif: binarized statistical image features. In: Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012), pp. 1363\u20131366. IEEE (2012)"},{"key":"17_CR23","doi-asserted-by":"publisher","first-page":"1957","DOI":"10.52202\/075280-0095","volume":"36","author":"M Kurmanji","year":"2023","unstructured":"Kurmanji, M., Triantafillou, P., Hayes, J., Triantafillou, E.: Towards unbounded machine unlearning. Adv. Neural. Inf. Process. Syst. 36, 1957\u20131987 (2023)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"17_CR24","unstructured":"Li, H., Ramachandra, R.: Deep features for contactless fingerprint presentation attack detection: Can they be generalized? In: Proceedings of the the Eight National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG 2023) Workshop (2023)"},{"key":"17_CR25","doi-asserted-by":"crossref","unstructured":"Li, H., Ramachandra, R.: Does capture background influence the accuracy of the deep learning based fingerphoto presentation attack detection techniques? In: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision, pp. 1034\u20131042 (2024)","DOI":"10.1109\/WACVW60836.2024.00113"},{"key":"17_CR26","doi-asserted-by":"crossref","unstructured":"Liu, Z., et al.: Swin transformer: hierarchical vision transformer using shifted windows. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 10012\u201310022 (2021)","DOI":"10.1109\/ICCV48922.2021.00986"},{"key":"17_CR27","doi-asserted-by":"crossref","unstructured":"Marasco, E., Vurity, A.: Fingerphoto presentation attack detection: generalization in smartphones. In: 2021 IEEE International Conference on Big Data (Big Data), pp. 4518\u20134523. IEEE (2021)","DOI":"10.1109\/BigData52589.2021.9672054"},{"issue":"22","key":"17_CR28","doi-asserted-by":"publisher","first-page":"11409","DOI":"10.3390\/app122211409","volume":"12","author":"E Marasco","year":"2022","unstructured":"Marasco, E., Vurity, A.: Late deep fusion of color spaces to enhance finger photo presentation attack detection in smartphones. Appl. Sci. 12(22), 11409 (2022)","journal-title":"Appl. Sci."},{"key":"17_CR29","doi-asserted-by":"crossref","unstructured":"Marasco, E., Vurity, A., Otham, A.: Deep color spaces for finger photo presentation attack detection in mobile devices. In: International Conference on Computer Vision and Image Processing, pp. 351\u2013362 (2021)","DOI":"10.1007\/978-3-031-11346-8_31"},{"key":"17_CR30","doi-asserted-by":"crossref","unstructured":"Nguyen, N.B., Chandrasegaran, K., Abdollahzadeh, M., man Cheung, N.: Label-only model inversion attacks via knowledge transfer. In: Thirty-seventh Conference on Neural Information Processing Systems (2023). https:\/\/openreview.net\/forum?id=NuoIThPPag","DOI":"10.52202\/075280-3015"},{"key":"17_CR31","unstructured":"Nguyen, T.T., et al.: A survey of machine unlearning. arXiv preprint arXiv:2209.02299 (2022)"},{"key":"17_CR32","doi-asserted-by":"crossref","unstructured":"Purnapatra, S., et al.: Presentation attack detection with advanced cnn models for noncontact-based fingerprint systems (2023)","DOI":"10.1109\/IWBF57495.2023.10157605"},{"key":"17_CR33","unstructured":"Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. International Conference on Learning Representations (ICLR) (2015)"},{"key":"17_CR34","unstructured":"State of California Department of Justice, Office of the Attorney General: California Consumer Privacy Act (CCPA) (2023). https:\/\/oag.ca.gov\/privacy\/ccpa, Accessed 20 March 2025"},{"key":"17_CR35","unstructured":"Tan, M., Le, Q.: Efficientnet: rethinking model scaling for convolutional neural networks. In: International Conference on Machine Learning, pp. 6105\u20136114. PMLR (2019)"},{"key":"17_CR36","doi-asserted-by":"publisher","unstructured":"Taneja, A., Tayal, A., Malhorta, A., Sankaran, A., Vatsa, M., Singh, R.: Fingerphoto spoofing in mobile devices: a preliminary study. In: 2016 IEEE 8th International Conference on Biometrics Theory, Applications and Systems (BTAS), pp.\u00a01\u20137 (2016). https:\/\/doi.org\/10.1109\/BTAS.2016.7791201","DOI":"10.1109\/BTAS.2016.7791201"},{"key":"17_CR37","doi-asserted-by":"crossref","unstructured":"Thudi, A., Deza, G., Chandrasekaran, V., Papernot, N.: Unrolling sgd: understanding factors influencing machine unlearning. In: 2022 IEEE 7th European Symposium on Security and Privacy (EuroS&P), pp. 303\u2013319. IEEE (2022)","DOI":"10.1109\/EuroSP53844.2022.00027"},{"key":"17_CR38","doi-asserted-by":"crossref","unstructured":"Voigt, P., Von\u00a0dem Bussche, A.: The eu general data protection regulation (gdpr). A practical guide, 1st ed., vol.10(3152676), pp. 10\u20135555. Springer International Publishing, Cham (2017)","DOI":"10.1007\/978-3-319-57959-7_1"},{"key":"17_CR39","doi-asserted-by":"publisher","unstructured":"Vurity, A., Marasco, E.: New finger photo databases with presentation attacks and demographics. In: 2023 IEEE International Conference on Big Data (BigData), pp. 2234\u20132242. (2023). https:\/\/doi.org\/10.1109\/BigData59044.2023.10386456","DOI":"10.1109\/BigData59044.2023.10386456"},{"key":"17_CR40","doi-asserted-by":"crossref","unstructured":"Vurity, A., Marasco, E., Ramachandra, R., Liao, D.: Interpreting the fraudulence level of different finger photo presentation attack instruments. In: IEEE International Conference on Image Processing (ICIP), pp. 1\u20137. (2024)","DOI":"10.1109\/ICIP51287.2024.10648169"},{"key":"17_CR41","doi-asserted-by":"crossref","unstructured":"Vurity, A., Marasco, E., Ramachandra, R., Park, J.: Colfigphotoattnnet: reliable finger photo presentation attack detection leveraging window-attention on color spaces. In: 2025 IEEE\/CVF Winter Conference on Applications of Computer Vision (WACV), pp. 5316\u20135325. IEEE (2025)","DOI":"10.1109\/WACV61041.2025.00519"},{"key":"17_CR42","unstructured":"Warnecke, A., Pirch, L., Wressnegger, C., Rieck, K.: Machine unlearning of features and labels, arXiv preprint arXiv:2108.11577 (2021)"},{"key":"17_CR43","doi-asserted-by":"crossref","unstructured":"Wild, P., Daubner, F., Penz, H., Dom\u00ednguez, G.F.: Comparative test of smartphone finger photo vs. touch-based cross-sensor fingerprint recognition. IEEE International Workshop on Biometrics and Forensics (IWBF), pp, 1\u20136 (2019)","DOI":"10.1109\/IWBF.2019.8739191"},{"key":"17_CR44","doi-asserted-by":"crossref","unstructured":"Yuan, X., Chen, K., Zhang, J., Zhang, W., Yu, N., Zhang, Y.: Pseudo label-guided model inversion attack via conditional generative adversarial network. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol.\u00a037, pp. 3349\u20133357 (2023)","DOI":"10.1609\/aaai.v37i3.25442"},{"key":"17_CR45","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Jia, R., Pei, H., Wang, W., Li, B., Song, D.: The secret revealer: generative model-inversion attacks against deep neural networks. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2020)","DOI":"10.1109\/CVPR42600.2020.00033"},{"key":"17_CR46","doi-asserted-by":"crossref","unstructured":"Zhou, Y., Zheng, D., Mo, Q., Lu, R., Lin, K.Y., Zheng, W.S.: Decoupled distillation to erase: a general unlearning method for any class-centric tasks. In: Proceedings of the Computer Vision and Pattern Recognition Conference, pp. 20350\u201320359 (2025)","DOI":"10.1109\/CVPR52734.2025.01895"}],"container-title":["Lecture Notes in Computer Science","Pattern Recognition"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-31930-2_17","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,2]],"date-time":"2026-08-02T05:42:06Z","timestamp":1785649326000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-31930-2_17"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8,3]]},"ISBN":["9783032319296","9783032319302"],"references-count":46,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-31930-2_17","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,8,3]]},"assertion":[{"value":"3 August 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICPR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Pattern Recognition","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Lyon","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"France","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2026","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 August 2026","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 August 2026","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icpr2026","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/icpr2026.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}