{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,18]],"date-time":"2026-07-18T21:02:22Z","timestamp":1784408542968,"version":"3.55.0"},"publisher-location":"Singapore","reference-count":24,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819233809","type":"print"},{"value":"9789819233816","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,7,19]],"date-time":"2026-07-19T00:00:00Z","timestamp":1784419200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,7,19]],"date-time":"2026-07-19T00:00:00Z","timestamp":1784419200000},"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\/978-981-92-3381-6_7","type":"book-chapter","created":{"date-parts":[[2026,7,18]],"date-time":"2026-07-18T20:15:46Z","timestamp":1784405746000},"page":"74-86","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["DCAD: Dual-Condition Adaptive Consistency Model for IoT Privacy-Preserving Video Anomaly Detection"],"prefix":"10.1007","author":[{"given":"Shaopeng","family":"Zhou","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chaohao","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haonan","family":"Yan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Feng","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Longlong","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chunming","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bin","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,7,19]]},"reference":[{"key":"7_CR1","first-page":"1","volume":"119","author":"European Parliament and Council","year":"2016","unstructured":"European Parliament and Council: Regulation (EU) 2016\/679 (General Data Protection Regulation). Off. J. Eur. Union. 119, 1\u201388 (2016)","journal-title":"Off. J. Eur. Union"},{"key":"7_CR2","unstructured":"Noghre, G.A., et al.: PHEVA: A privacy-preserving human-centric video anomaly detection dataset. arXiv preprint https:\/\/arxiv.org\/abs\/2408.14329 (2024)"},{"key":"7_CR3","first-page":"6840","volume":"33","author":"J Ho","year":"2020","unstructured":"Ho, J., Jain, A., Abbeel, P.: Denoising diffusion probabilistic models. Adv. Neural Inf. Proces. Syst. 33, 6840\u20136851 (2020)","journal-title":"Adv. Neural Inf. Proces. Syst."},{"key":"7_CR4","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2024.127726","volume":"591","author":"YA Samaila","year":"2024","unstructured":"Samaila, Y.A., et al.: Video anomaly detection: a systematic review of issues and prospects. Neurocomputing. 591, 127726 (2024)","journal-title":"Neurocomputing"},{"key":"7_CR5","first-page":"1","volume":"57","author":"J Liu","year":"2025","unstructured":"Liu, J., et al.: Networking systems for video anomaly detection: a tutorial and survey. ACM Comput. Surv. 57, 1\u201337 (2025)","journal-title":"ACM Comput. Surv."},{"key":"7_CR6","doi-asserted-by":"crossref","unstructured":"Georgescu, M.I., Barbalau, A., Ionescu, R.T., Khan, F.S., Popescu, M., Shah, M.: Anomaly detection in video via self-supervised and multi-task learning. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 12742\u201312752 (2021),","DOI":"10.1109\/CVPR46437.2021.01255"},{"key":"7_CR7","first-page":"1","volume-title":"2025 IEEE International Conference on Multimedia and Expo (ICME)","author":"J Lyu","year":"2025","unstructured":"Lyu, J., Zhao, M., Hu, J., Huang, X., Chen, Y., Du, S.: VadMamba: Exploring state space models for fast video anomaly detection. In: 2025 IEEE International Conference on Multimedia and Expo (ICME), pp. 1\u20136. IEEE (2025)"},{"key":"7_CR8","unstructured":"Song, Y., Dhariwal, P., Chen, M., Sutskever, I.: Consistency models. International Conference on Machine Learning (ICML). (2023)"},{"key":"7_CR9","doi-asserted-by":"crossref","unstructured":"Morais, R., Le, V., Tran, T., Saha, B., Mansour, M., Venkatesh, S.: Learning regularity in skeleton trajectories for anomaly detection in videos. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 11996\u201312004 (2019).","DOI":"10.1109\/CVPR.2019.01227"},{"key":"7_CR10","doi-asserted-by":"crossref","unstructured":"Hirschorn, O., Avidan, S.: Normalizing flows for human pose anomaly detection. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV). pp. 13545\u201313554 (2023).","DOI":"10.1109\/ICCV51070.2023.01246"},{"key":"7_CR11","doi-asserted-by":"crossref","unstructured":"Deli\u0107, A., Grcic, M., \u0160egvi\u0107, S.: Sequential keypoint density estimator: An overlooked baseline of skeleton-based video anomaly detection. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV). pp. 11579\u201311589 (2025).","DOI":"10.1109\/ICCV51701.2025.01077"},{"key":"7_CR12","doi-asserted-by":"crossref","unstructured":"Wyatt, J., Leach, A., Schmon, S.M., Willcocks, C.G.: AnoDDPM: Anomaly detection with denoising diffusion probabilistic models using simplex noise. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 650\u2013656 (2022).","DOI":"10.1109\/CVPRW56347.2022.00080"},{"key":"7_CR13","doi-asserted-by":"crossref","unstructured":"Zhang, H., Wang, Z., Zeng, D., Wu, Z., Jiang, Y.G.: DiffusionAD: norm-guided one-step denoising diffusion for anomaly detection. IEEE Trans. Pattern Anal. Mach. Intell. (2025)","DOI":"10.1109\/TPAMI.2025.3570494"},{"key":"7_CR14","doi-asserted-by":"crossref","unstructured":"Liu, W., Chang, H., Ma, B., Shan, S., Chen, X.: Diversity-measurable anomaly detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 12147\u201312156 (2023).","DOI":"10.1109\/CVPR52729.2023.01169"},{"key":"7_CR15","doi-asserted-by":"publisher","first-page":"17825","DOI":"10.1007\/s00521-025-11218-1","volume":"37","author":"E Dilek","year":"2025","unstructured":"Dilek, E., Dener, M.: An overview of transformers for video anomaly detection. Neural Comput. & Applic. 37, 17825\u201317857 (2025)","journal-title":"Neural Comput. & Applic."},{"key":"7_CR16","doi-asserted-by":"crossref","unstructured":"Wang, B., Huang, C., Wen, J., Wang, W., Liu, Y., Xu, Y.: Federated weakly supervised video anomaly detection with multimodal prompt. In: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI). pp. 21017\u201321025 (2025).","DOI":"10.1609\/aaai.v39i20.35398"},{"key":"7_CR17","doi-asserted-by":"crossref","unstructured":"Fioresi, J., Dave, I.R., Shah, M.: TED-SPAD: Temporal distinctiveness for self-supervised privacy-preservation for video anomaly detection. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV). pp. 13598\u201313609 (2023).","DOI":"10.1109\/ICCV51070.2023.01251"},{"key":"7_CR18","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2023.110872","volume":"278","author":"Y Su","year":"2023","unstructured":"Su, Y., Zhu, H., Tan, Y., An, S., Xing, M.: PRIME: privacy-preserving video anomaly detection via motion exemplar guidance. Knowl.-Based Syst. 278, 110872 (2023)","journal-title":"Knowl.-Based Syst."},{"key":"7_CR19","doi-asserted-by":"publisher","DOI":"10.1016\/j.comnet.2025.111376","volume":"268","author":"I Rasheed","year":"2025","unstructured":"Rasheed, I., Mostafa, H.: Federated learning-based anomaly detection for zero-day attack prevention in 6G network slices. Comput. Netw. 268, 111376 (2025)","journal-title":"Comput. Netw."},{"key":"7_CR20","first-page":"695","volume":"85","author":"MN Alatawi","year":"2025","unstructured":"Alatawi, M.N.: EdgeGuard-IoT: 6G-enabled edge intelligence for secure federated learning and adaptive anomaly detection in Industry 5.0. Comput. Mater. Contin. 85, 695\u2013727 (2025)","journal-title":"Comput. Mater. Contin."},{"key":"7_CR21","unstructured":"Li, J., et al.: Video anomaly detection with semantics-aware information bottleneck. arXiv preprint https:\/\/arxiv.org\/abs\/2506.02535 (2025)."},{"key":"7_CR22","unstructured":"Salimans, T., Ho, J.: Progressive distillation for fast sampling of diffusion models. International Conference on Learning Representations (ICLR). (2022)"},{"key":"7_CR23","doi-asserted-by":"crossref","unstructured":"Liu, W., Luo, W., Lian, D., Gao, S.: Future frame prediction for anomaly detection-a new baseline. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pp. 6536\u20136545 (2018).","DOI":"10.1109\/CVPR.2018.00684"},{"key":"7_CR24","doi-asserted-by":"crossref","unstructured":"Lu, C., Shi, J., Jia, J.: Abnormal event detection at 150 FPS in MATLAB. In: Proceedings of the IEEE International Conference on Computer Vision (ICCV). pp. 2720\u20132727 (2013).","DOI":"10.1109\/ICCV.2013.338"}],"container-title":["Lecture Notes in Computer Science","Advanced Intelligent Computing Technology and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-92-3381-6_7","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,18]],"date-time":"2026-07-18T20:15:49Z","timestamp":1784405749000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-92-3381-6_7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,19]]},"ISBN":["9789819233809","9789819233816"],"references-count":24,"URL":"https:\/\/doi.org\/10.1007\/978-981-92-3381-6_7","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,19]]},"assertion":[{"value":"19 July 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Toronto","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Canada","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":"22 July 2026","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 July 2026","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icic2026a","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ic-icc.cn\/2026\/index.htm","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}