{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T19:38:07Z","timestamp":1757619487503,"version":"3.44.0"},"publisher-location":"Singapore","reference-count":39,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819698653"},{"type":"electronic","value":"9789819698660"}],"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\/978-981-96-9866-0_35","type":"book-chapter","created":{"date-parts":[[2025,7,23]],"date-time":"2025-07-23T09:26:01Z","timestamp":1753262761000},"page":"406-417","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Frequency-Domain Enhanced Adaptive Ensemble Adversarial Attack for Protecting Image Privacy"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-7431-7002","authenticated-orcid":false,"given":"Zengchao","family":"Duan","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8458-6704","authenticated-orcid":false,"given":"Zheng","family":"Wang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8691-8677","authenticated-orcid":false,"given":"Meijun","family":"Sun","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,7,24]]},"reference":[{"key":"35_CR1","unstructured":"Szegedy, C., Zaremba, W., Sutskever, I., et al.: Intriguing properties of neural networks. In: International Conference on Learning Representations, pp. 1\u201310. Curran Associates, Inc., Red Hook (2014)"},{"key":"35_CR2","unstructured":"Ru, B., Cobb, A., Blaas, A., et al.: BayesOpt adversarial attack. In: International Conference on Learning Representations, pp. 1\u201317. Curran Associates, Inc., Red Hook (2020)"},{"key":"35_CR3","doi-asserted-by":"crossref","unstructured":"Rahmati, A., Moosavi-Dezfooli, S.M., Frossard, P., et al.: GeoDA: a geometric framework for black-box adversarial attacks. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, Los Alamitos, pp. 8446\u20138455. IEEE (2020)","DOI":"10.1109\/CVPR42600.2020.00847"},{"key":"35_CR4","doi-asserted-by":"crossref","unstructured":"Ma, W., Li, Y., Jia, X., et al.: Transferable adversarial attack for both vision transformers and convolutional networks via momentum integrated gradients. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, Los Alamitos, pp. 4630\u20134639. IEEE (2023)","DOI":"10.1109\/ICCV51070.2023.00427"},{"key":"35_CR5","unstructured":"Wang, X., Tong, K., He, K.: Rethinking the backward propagation for adversarial transferability. In: Advances in Neural Information Processing Systems, pp. 1905\u20131922 (2023)"},{"key":"35_CR6","doi-asserted-by":"crossref","unstructured":"Wang, R., Guo, Y., Wang, Y.: AGS: affordable and generalizable substitute training for transferable adversarial attack. In: Proceedings of the AAAI Conference on Artificial Intelligence, Palo Alto, CA, pp. 5553\u20135562. AAAI Press (2024)","DOI":"10.1609\/aaai.v38i6.28365"},{"key":"35_CR7","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2024.124757","volume":"255","author":"J Wang","year":"2024","unstructured":"Wang, J., Chen, Z., Jiang, K., et al.: Boosting the transferability of adversarial attacks with global momentum initialization. Expert Syst. Appl. 255, 124757 (2024)","journal-title":"Expert Syst. Appl."},{"key":"35_CR8","doi-asserted-by":"crossref","unstructured":"Dong, Y., Liao, F., Pang, T., et al.: Boosting adversarial attacks with momentum. In: IEEE Conference on Computer Vision and Pattern Recognition, Los Alamitos, pp. 9185\u20139193. IEEE (2018)","DOI":"10.1109\/CVPR.2018.00957"},{"key":"35_CR9","doi-asserted-by":"crossref","unstructured":"Wang, X., Zhang, Z., Zhang, J.: Structure invariant transformation for better adversarial transferability. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, Los Alamitos, pp. 4607\u20134619. IEEE (2023)","DOI":"10.1109\/ICCV51070.2023.00425"},{"key":"35_CR10","doi-asserted-by":"crossref","unstructured":"Ge, Z., Shang, F., Liu, H., et al.: Improving the transferability of adversarial examples with arbitrary style transfer. In: Proceedings of the 31st ACM International Conference on Multimedia, New York, pp. 4440\u20134449. ACM (2023)","DOI":"10.1145\/3581783.3612070"},{"key":"35_CR11","doi-asserted-by":"crossref","unstructured":"Wang, K., He, X., Wang, W., et al.: Boosting adversarial transferability by block shuffle and rotation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, Los Alamitos, pp. 24336\u201324346. IEEE (2024)","DOI":"10.1109\/CVPR52733.2024.02297"},{"key":"35_CR12","doi-asserted-by":"crossref","unstructured":"Lin, Q., Luo, C., Niu, Z., et al.: Boosting adversarial transferability across model genus by deformation-constrained warping. In: Proceedings of the AAAI Conference on Artificial Intelligence, Palo Alto, CA, pp. 3459\u20133467. AAAI Press (2024)","DOI":"10.1609\/aaai.v38i4.28133"},{"key":"35_CR13","unstructured":"Liu, Y., Chen, X., Liu, C., et al.: Delving into transferable adversarial examples and black-box attacks. In: International Conference on Learning Representations, pp. 1\u201314. Curran Associates, Inc., Red Hook (2017)"},{"key":"35_CR14","doi-asserted-by":"crossref","unstructured":"Xiong, Y., Lin, J., Zhang, M., et al.: Stochastic variance reduced ensemble adversarial attack for boosting the adversarial transferability. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, Los Alamitos, pp. 14983\u201314992. IEEE (2022)","DOI":"10.1109\/CVPR52688.2022.01456"},{"key":"35_CR15","doi-asserted-by":"crossref","unstructured":"Chen, B., Yin, J., Chen, S., et al.: An adaptive model ensemble adversarial attack for boosting adversarial transferability. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, Los Alamitos, pp. 4489\u20134498. IEEE (2023)","DOI":"10.1109\/ICCV51070.2023.00414"},{"key":"35_CR16","unstructured":"Yin, D., Gontijo Lopes, R., Shlens, J., et al.: A Fourier perspective on model robustness in computer vision. In: Advances in Neural Information Processing Systems, vol. 32, pp. 13276\u201313286 (2019)"},{"key":"35_CR17","doi-asserted-by":"publisher","unstructured":"Long, Y., et al.: Frequency domain model augmentation for\u00a0adversarial attack. In: Avidan, S., Brostow, G., Ciss\u00e9, M., Farinella, G.M., Hassner, T. (eds.) ECCV 2022. LNCS, vol. 13664, pp. 549\u2013566. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-19772-7_32","DOI":"10.1007\/978-3-031-19772-7_32"},{"key":"35_CR18","doi-asserted-by":"publisher","unstructured":"Lv, S., Liu, Y., Sun, J.: IMES: an automatically scalable invisible membrane image encryption for privacy protection on IoT sensors. In: Vaidya, J., Zhang, X., Li, J. (eds.) CSS 2019. LNCS, vol. 11982, pp. 265\u2013273. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-37337-5_21","DOI":"10.1007\/978-3-030-37337-5_21"},{"key":"35_CR19","doi-asserted-by":"publisher","first-page":"83596","DOI":"10.1109\/ACCESS.2020.2991420","volume":"8","author":"Q Liu","year":"2020","unstructured":"Liu, Q., Liu, L.: Color image encryption algorithm based on DNA coding and double chaos system. IEEE Access 8, 83596\u201383610 (2020)","journal-title":"IEEE Access"},{"key":"35_CR20","doi-asserted-by":"crossref","unstructured":"Zhang, J., Ye, M., Yang, Y.: Learnable privacy-preserving anonymization for pedestrian images. In: 30th ACM International Conference on Multimedia, pp. 7300\u20137308, New York. ACM (2022)","DOI":"10.1145\/3503161.3548766"},{"key":"35_CR21","doi-asserted-by":"publisher","unstructured":"Hukkel\u00e5s, H., Mester, R., Lindseth, F.: DeepPrivacy: a generative adversarial network for face anonymization. In: Bebis, G., et al.: ISVC 2019. LNCS, vol. 11844, pp. 565\u2013578. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-33720-9_44","DOI":"10.1007\/978-3-030-33720-9_44"},{"key":"35_CR22","doi-asserted-by":"crossref","unstructured":"Hukkel\u00e5s, H., Lindseth, F.: DeepPrivacy2: towards realistic full-body anonymization. In: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision, Los Alamitos, pp. 1329\u20131338. IEEE (2023)","DOI":"10.1109\/WACV56688.2023.00138"},{"key":"35_CR23","doi-asserted-by":"crossref","unstructured":"Klemp, M., R\u00f6sch, K., Wagner, R., et al.: LDFA: latent diffusion face anonymization for self-driving applications. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, Los Alamitos, pp. 3199\u20133205. IEEE (2023)","DOI":"10.1109\/CVPRW59228.2023.00322"},{"key":"35_CR24","doi-asserted-by":"crossref","unstructured":"Yang, X., Dong, Y., Pang, T., et al.: Towards face encryption by generating adversarial identity masks. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, Los Alamitos, pp. 3897\u20133907. IEEE (2021)","DOI":"10.1109\/ICCV48922.2021.00387"},{"key":"35_CR25","doi-asserted-by":"publisher","first-page":"20757","DOI":"10.1109\/JIOT.2024.3373636","volume":"2024","author":"Z Chen","year":"2024","unstructured":"Chen, Z., Chai, X., Gan, Z., et al.: RAE-VWP: a reversible adversarial example-based privacy and copyright protection method of medical images for Internet of Medical Things. IEEE Internet Things J. 2024, 20757\u201320768 (2024)","journal-title":"IEEE Internet Things J."},{"key":"35_CR26","unstructured":"Goodfellow, I.J., Shlens, J., Szegedy, C.: Explaining and harnessing adversarial examples. In: International Conference on Learning Representations, pp. 1\u201311. Curran Associates, Inc., Red Hook (2015)"},{"key":"35_CR27","unstructured":"Kurakin, A., Goodfellow, I.J., Bengio, S.: Adversarial machine learning at scale. In: International Conference on Learning Representations, pp. 1\u201315. Curran Associates, Inc., Red Hook (2017)"},{"key":"35_CR28","unstructured":"Madry, A., Makelov, A., Schmidt, L., et al.: Towards deep learning models resistant to adversarial attacks. In: International Conference on Learning Representations (ICLR), pp. 142\u2013165. Curran Associates, Inc., Red Hook (2018)"},{"key":"35_CR29","doi-asserted-by":"crossref","unstructured":"Sharma Y, Ding G W, Brubaker M.: On the effectiveness of low frequency perturbations. In: Proceedings of the 28th International Joint Conference on Artificial Intelligence, Palo Alto, CA, pp. 3389\u20133396. AAAI Press (2019)","DOI":"10.24963\/ijcai.2019\/470"},{"issue":"90","key":"35_CR30","doi-asserted-by":"publisher","first-page":"297","DOI":"10.1090\/S0025-5718-1965-0178586-1","volume":"19","author":"JW Cooley","year":"1965","unstructured":"Cooley, J.W., Tukey, J.W.: An algorithm for the machine calculation of complex Fourier series. Math. Comput. 19(90), 297\u2013301 (1965)","journal-title":"Math. Comput."},{"issue":"7","key":"35_CR31","doi-asserted-by":"publisher","first-page":"909","DOI":"10.1002\/cpa.3160410705","volume":"41","author":"I Daubechies","year":"1988","unstructured":"Daubechies, I.: Orthonormal bases of compactly supported wavelets. Commun. Pure Appl. Math. 41(7), 909\u2013996 (1988)","journal-title":"Commun. Pure Appl. Math."},{"issue":"1","key":"35_CR32","doi-asserted-by":"publisher","first-page":"90","DOI":"10.1109\/T-C.1974.223784","volume":"100","author":"N Ahmed","year":"1974","unstructured":"Ahmed, N., Natarajan, T.R., Rao, K.R.: Discrete cosine transform. IEEE Trans. Comput. 100(1), 90\u201393 (1974)","journal-title":"IEEE Trans. Comput."},{"key":"35_CR33","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., et al.: Deep residual learning for image recognition. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, Los Alamitos, pp. 770\u2013778. IEEE (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"35_CR34","doi-asserted-by":"crossref","unstructured":"Szegedy, C., Vanhoucke, V., Ioffe, S., et al.: Rethinking the inception architecture for computer vision. In: IEEE Conference on Computer Vision and Pattern Recognition, Los Alamitos, pp. 2818\u20132826. IEEE (2016)","DOI":"10.1109\/CVPR.2016.308"},{"key":"35_CR35","unstructured":"Dosovitskiy, A., Beyer, L., Kolesnikov, A., et al.: An image is worth 16x16 words: transformers for image recognition at scale. In: International Conference on Learning Representations, pp. 271\u2013291. Curran Associates, Inc., Red Hook (2021)"},{"key":"35_CR36","unstructured":"Touvron, H., Cord, M., Douze, M., et al.: Training data-efficient image transformers & distillation through attention. In: International Conference on Machine Learning, Baltimore, pp. 10347\u201310357. PMLR (2021)"},{"key":"35_CR37","doi-asserted-by":"publisher","unstructured":"Kolesnikov, A., et al.: Big transfer (BiT): general visual representation learning. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.M. (eds.) ECCV 2020. LNCS, vol. 12350, pp. 491\u2013507. Springer, Cham. https:\/\/doi.org\/10.1007\/978-3-030-58558-7_29","DOI":"10.1007\/978-3-030-58558-7_29"},{"key":"35_CR38","doi-asserted-by":"crossref","unstructured":"Wang, X., He, X., Wang, J., et al.: Admix: enhancing the transferability of adversarial attacks. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, Los Alamitos, pp. 16158\u201316167. IEEE (2021)","DOI":"10.1109\/ICCV48922.2021.01585"},{"key":"35_CR39","unstructured":"Guo, C., Rana, M., Cisse, M., van der Maaten, L.: Countering adversarial images using input transformations. In: International Conference on Learning Representations, pp. 1\u201312. Curran Associates, Inc., Red Hook (2018)"}],"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\/978-981-96-9866-0_35","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,7]],"date-time":"2025-09-07T19:45:09Z","timestamp":1757274309000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-96-9866-0_35"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9789819698653","9789819698660"],"references-count":39,"URL":"https:\/\/doi.org\/10.1007\/978-981-96-9866-0_35","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":"24 July 2025","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":"Ningbo","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":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 July 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 July 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icic2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ic-icc.cn\/icg\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}