{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T14:33:56Z","timestamp":1775745236770,"version":"3.50.1"},"publisher-location":"Singapore","reference-count":26,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819784868","type":"print"},{"value":"9789819784875","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,11,4]],"date-time":"2024-11-04T00:00:00Z","timestamp":1730678400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,11,4]],"date-time":"2024-11-04T00:00:00Z","timestamp":1730678400000},"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\/978-981-97-8487-5_26","type":"book-chapter","created":{"date-parts":[[2024,11,3]],"date-time":"2024-11-03T07:03:44Z","timestamp":1730617424000},"page":"367-379","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["TRAE: Reversible Adversarial Example with\u00a0Traceability"],"prefix":"10.1007","author":[{"given":"Zhuo","family":"Tian","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoyi","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fan","family":"Xing","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wentao","family":"Hao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ruiyang","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,11,4]]},"reference":[{"key":"26_CR1","doi-asserted-by":"crossref","unstructured":"Jiang, H., Diao, Z., Shi, T., Zhou, Y., Wang, F., Hu, W., Zhu, X., Luo, S., Tong, G., Yao, Y.D.: A review of deep learning-based multiple-lesion recognition from medical images: classification, detection and segmentation. In: Computers in Biology and Medicine, p. 106726 (2023)","DOI":"10.1016\/j.compbiomed.2023.106726"},{"key":"26_CR2","doi-asserted-by":"crossref","unstructured":"Chowdhury, S.H., Sany, M.R., Ahamed, M.H., Das, S.K., Badal, F.R., Das, P., Tasneem, Z., Hasan, M.M., Islam, M.R., Ali, M.F., et\u00a0al.: A state-of-the-art computer vision adopting non-Euclidean deep-learning models. Int. J. Intell. Syst. (2023)","DOI":"10.1155\/2023\/8674641"},{"key":"26_CR3","doi-asserted-by":"crossref","unstructured":"Lavorgna, A., Ugwudike, P., Tartari, M.: Online sharenting: Identifying existing vulnerabilities and demystifying media reported crime risks. Crime Med. Culture 17416590221148448 (2023)","DOI":"10.1177\/17416590221148448"},{"issue":"5","key":"26_CR4","doi-asserted-by":"publisher","first-page":"1975","DOI":"10.1007\/s00371-022-02459-5","volume":"39","author":"P Fang","year":"2023","unstructured":"Fang, P., Liu, H., Wu, C., Liu, M.: A survey of image encryption algorithms based on chaotic system. Vis. Comput. 39(5), 1975\u20132003 (2023)","journal-title":"Vis. Comput."},{"key":"26_CR5","unstructured":"Szegedy, C., Zaremba, W., Sutskever, I., Bruna, J., Erhan, D., Goodfellow, I., Fergus, R.: Intriguing properties of neural networks (2013). arXiv:1312.6199"},{"issue":"4","key":"26_CR6","doi-asserted-by":"publisher","first-page":"1473","DOI":"10.1109\/TCYB.2018.2882908","volume":"50","author":"E Yang","year":"2018","unstructured":"Yang, E., Liu, T., Deng, C., Tao, D.: Adversarial examples for hamming space search. IEEE Trans. Cybern. 50(4), 1473\u20131484 (2018)","journal-title":"IEEE Trans. Cybern."},{"key":"26_CR7","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2022.109048","volume":"134","author":"J Liu","year":"2023","unstructured":"Liu, J., Zhang, W., Fukuchi, K., Akimoto, Y., Sakuma, J.: Unauthorized AI cannot recognize me: Reversible adversarial example. Pattern Recogn. 134, 109048 (2023)","journal-title":"Pattern Recogn."},{"issue":"2","key":"26_CR8","doi-asserted-by":"publisher","first-page":"562","DOI":"10.1109\/TCSVT.2022.3207008","volume":"33","author":"J Zhang","year":"2022","unstructured":"Zhang, J., Wang, J., Wang, H., Luo, X.: Self-recoverable adversarial examples: a new effective protection mechanism in social networks. IEEE Trans. Circuits Syst. Video Technol. 33(2), 562\u2013574 (2022)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"26_CR9","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2023.109549","volume":"140","author":"L Xiong","year":"2023","unstructured":"Xiong, L., Wu, Y., Yu, P., Zheng, Y.: A black-box reversible adversarial example for authorizable recognition to shared images. Pattern Recogn. 140, 109549 (2023)","journal-title":"Pattern Recogn."},{"key":"26_CR10","doi-asserted-by":"crossref","unstructured":"Hou, D., Zhang, W., Liu, J., Zhou, S., Chen, D., Yu, N.: Emerging applications of reversible data hiding. In: Proceedings of the 2nd International Conference on Image and Graphics Processing, pp. 105\u2013109 (2019)","DOI":"10.1145\/3313950.3313952"},{"key":"26_CR11","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.patrec.2022.12.018","volume":"166","author":"Z Yin","year":"2023","unstructured":"Yin, Z., Chen, L., Lyu, W., Luo, B.: Reversible attack based on adversarial perturbation and reversible data hiding in YUV colorspace. Pattern Recogn. Lett. 166, 1\u20137 (2023)","journal-title":"Pattern Recogn. Lett."},{"key":"26_CR12","doi-asserted-by":"crossref","unstructured":"Selvaraju, R.R., Cogswell, M., Das, A., Vedantam, R., Parikh, D., Batra, D.: Grad-CAM: visual explanations from deep networks via gradient-based localization. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 618\u2013626 (2017)","DOI":"10.1109\/ICCV.2017.74"},{"issue":"6","key":"26_CR13","doi-asserted-by":"publisher","first-page":"7298","DOI":"10.1007\/s10489-022-03926-1","volume":"53","author":"M Xue","year":"2023","unstructured":"Xue, M., Wu, Y., Zhang, Y., Wang, J., Liu, W.: Dataset authorization control: protect the intellectual property of dataset via reversible feature space adversarial examples. Appl. Intell. 53(6), 7298\u20137309 (2023)","journal-title":"Appl. Intell."},{"issue":"8","key":"26_CR14","doi-asserted-by":"publisher","first-page":"1469","DOI":"10.1109\/TMM.2016.2569497","volume":"18","author":"W Zhang","year":"2016","unstructured":"Zhang, W., Wang, H., Hou, D., Yu, N.: Reversible data hiding in encrypted images by reversible image transformation. IEEE Trans. Multimed. 18(8), 1469\u20131479 (2016)","journal-title":"IEEE Trans. Multimed."},{"key":"26_CR15","doi-asserted-by":"crossref","unstructured":"Li, C.Y., S\u00e1nchez-Matilla, R., Shamsabadi, A.S., Mazzon, R., Cavallaro, A.: On the reversibility of adversarial attacks. In: 2021 IEEE International Conference on Image Processing (ICIP), pp. 3073\u20133077 (2021). 10.1109\/ICIP42928.2021.9506451","DOI":"10.1109\/ICIP42928.2021.9506451"},{"key":"26_CR16","doi-asserted-by":"crossref","unstructured":"Ernawan, F., Ariatmanto, D.: A recent survey on image watermarking using scaling factor techniques for copyright protection. Multimed. Tools Appl. 1\u201341 (2023)","DOI":"10.1007\/s11042-023-14447-5"},{"issue":"2","key":"26_CR17","first-page":"1148","volume":"29","author":"MT Gaata","year":"2023","unstructured":"Gaata, M.T., Al-Hassani, M.D.: Underwater image copyright protection using robust watermarking technique. Indones. J. Electr. Eng. Comput. Sci. 29(2), 1148\u20131156 (2023)","journal-title":"Indones. J. Electr. Eng. Comput. Sci."},{"issue":"2","key":"26_CR18","doi-asserted-by":"publisher","first-page":"2237","DOI":"10.1007\/s11042-022-13314-z","volume":"82","author":"P Garg","year":"2023","unstructured":"Garg, P., Jain, A.: A robust technique for biometric image authentication using invisible watermarking. Multimed. Tools Appl. 82(2), 2237\u20132253 (2023)","journal-title":"Multimed. Tools Appl."},{"key":"26_CR19","doi-asserted-by":"crossref","unstructured":"Zhu, J., Kaplan, R., Johnson, J., Fei-Fei, L.: Hidden: hiding data with deep networks. In: Proceedings of the European Conference on Computer Vision (ECCV), pp. 657\u2013672 (2018)","DOI":"10.1007\/978-3-030-01267-0_40"},{"key":"26_CR20","doi-asserted-by":"crossref","unstructured":"Fang, H., Qiu, Y., Chen, K., Zhang, J., Zhang, W., Chang, E.C.: Flow-based robust watermarking with invertible noise layer for black-box distortions. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol.\u00a037, pp. 5054\u20135061 (2023)","DOI":"10.1609\/aaai.v37i4.25633"},{"key":"26_CR21","doi-asserted-by":"crossref","unstructured":"Fang, H., Jia, Z., Ma, Z., Chang, E.C., Zhang, W.: Pimog: an effective screen-shooting noise-layer simulation for deep-learning-based watermarking network. In: Proceedings of the 30th ACM International Conference on Multimedia, pp. 2267\u20132275 (2022)","DOI":"10.1145\/3503161.3548049"},{"key":"26_CR22","unstructured":"Le, Y., Yang, X.: Tiny imagenet visual recognition challenge. CS 231N 7(7), 3 (2015)"},{"key":"26_CR23","unstructured":"Griffin, G., Holub, A., Perona, P.: Caltech-256 object category dataset. California Institute of Technology (2007)"},{"key":"26_CR24","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":"26_CR25","doi-asserted-by":"crossref","unstructured":"Szegedy, C., Vanhoucke, V., Ioffe, S., Shlens, J., Wojna, Z.: Rethinking the inception architecture for computer vision. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2818\u20132826 (2016)","DOI":"10.1109\/CVPR.2016.308"},{"key":"26_CR26","unstructured":"Paszke, A., Gross, S., Massa, F., Lerer, A., Bradbury, J., Chanan, G., Killeen, T., Lin, Z., Gimelshein, N., Antiga, L., et\u00a0al.: Pytorch: an imperative style, high-performance deep learning library. Adv. Neural Inf. Process. Syst. 32 (2019)"}],"container-title":["Lecture Notes in Computer Science","Pattern Recognition and Computer Vision"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-97-8487-5_26","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,3]],"date-time":"2024-11-03T07:09:14Z","timestamp":1730617754000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-97-8487-5_26"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,4]]},"ISBN":["9789819784868","9789819784875"],"references-count":26,"URL":"https:\/\/doi.org\/10.1007\/978-981-97-8487-5_26","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,11,4]]},"assertion":[{"value":"4 November 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PRCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Chinese Conference on Pattern Recognition and Computer Vision  (PRCV)","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Urumqi","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":"18 October 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20 October 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ccprcv2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/2024.prcv.cn\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}