디지털 시대의 익명성: 얼굴 인식의 비식별화 및 재식별화 기술

  • Published : 2023.06.30

Abstract

Keywords

References

  1. M. Shen, Y. Deng, L. Zhu, X. Du, and N. Guizani, "Privacy-preserving image retrieval for medical IoT systems: A block-chain-based approach," IEEE Netw., Vol. 33, No. 5, pp. 27-33, 2019. https://doi.org/10.1109/MNET.001.1800503
  2. D. M. Lazer, A. Pentland, D. J. Watts, S. Aral, S. Athey, N. Contractor, and C. Wagner, "Computational social science: Obstacles and opportunities," Science, Vol. 369, No. 6507, pp. 1060-1062, 2020. https://doi.org/10.1126/science.aaz8170
  3. Y. L. Pan, J. C. Chen, and J.. L. Wu, "Towards a Controllable and Reversible Privacy Protection System for Facial Images through Enhanced Multi-Factor Modifier Networks," Entropy, Vol. 25, No. 2, pp. 272, 2023.
  4. M. N. Asghar, N. Kanwal, B. Lee, M. Fleury, M. Herbst, and Y. Qiao, "Visual surveillance within the EU general data protection regulation: A technology perspective," IEEE Access, Vol. 7, pp. 111709-111726, 2019. https://doi.org/10.1109/ACCESS.2019.2934226
  5. Y. Mekdad, A. Aris, L. Babun, A. El Fergougui, M. Conti, R. Lazzeretti, and A. S. Uluagac, "A survey on security and privacy issues of UAVs," Comput. Netw., Vol. 224, 109626, 2023.
  6. X. Jiang, F. R. Yu, T. Song, and V. C. Leung, "Resource allocation of video streaming over vehicular networks: A survey, some research issues and challenges," IEEE Trans. Intell. Transp. Syst., Vol. 23, No. 7, pp. 5955-5975, 2021.
  7. J. M. Blythe and S. D. Johnson, "A systematic review of crime facilitated by the consumer Internet of Things," Secur. J., Vol. 34, pp. 97-125, 2021. https://doi.org/10.1057/s41284-019-00211-8
  8. B. Liu, M. Ding, S. Shaham, W. Rahayu, F. Farokhi, and Z. Lin, "When machine learning meets privacy: A survey and outlook," ACM Comput. Surv., Vol. 54, No. 2, pp. 1-36, 2021. https://doi.org/10.1145/3436755
  9. M. H. P. Rizi and S. A. H. Seno, "A systematic review of technologies and solutions to improve security and privacy protection of citizens in the smart city," Internet Things, pp. 100584, 2022.
  10. D. Ling, Z. Wei, F. Huazhu, R. Wenqi, and Z. Xinpeng, "An efficient privacy protection scheme for data security in video surveillance," J. Vis. Commun. Image Represent., Vol. 59, pp. 347-362, 2019. https://doi.org/10.1016/j.jvcir.2019.01.027
  11. Z. Guo and L. Kennedy, "Policing based on automatic facial recognition," Artif. Intell. Law, Vol. 31, No. 2, pp. 397-443, 2023. https://doi.org/10.1007/s10506-022-09330-x
  12. H. Cai, J. Lin, Y. Lin, Z. Liu, H. Tang, H. Wang, and S. Han, "Enable deep learning on mobile devices: Methods, systems, and applications," ACM Trans. Des. Autom. Electron. Syst., Vol. 27, No. 3, pp. 1-50, 2022. https://doi.org/10.1145/3486618
  13. A. Fitwi, Y. Chen, S. Zhu, E. Blasch, and G. Chen, "Privacy-preserving surveillance as an edge service based on lightweight video protection schemes using face de-identification and window masking," Electronics, Vol. 10, No. 3, pp. 236, 2021.
  14. F. Schroff, D. Kalenichenko, and J. Philbin, "FaceNet: A unified embedding for face recognition and clustering," in Proc. IEEE Conf. Comput. Vision Pattern Recognit., pp. 815-823, 2015.
  15. K. Zhang, Z. Zhang, Z. Li, and Y. Qiao, "Joint face detection and alignment using multitask cascaded convolutional networks," IEEE Signal Process. Lett., Vol. 23, No. 10, pp. 1499-1503, 2016. https://doi.org/10.1109/LSP.2016.2603342
  16. P. Mettes, D. C. Koelma, and C. G. Snoek, "Shuffled ImageNet banks for video event detection and search," ACM Trans. Multimedia Comput. Commun. Appl., Vol. 16, No. 2, pp. 1-21, 2020. https://doi.org/10.1145/3377875
  17. B. Zhang, B. Rahmatullah, S. L. Wang, A. A. Zaidan, B. B. Zaidan, and P. Liu, "A review of research on medical image confidentiality related technology coherent taxonomy, motivations, open challenges and recommendations," Multimedia Tools Appl., Vol. 82, pp. 21867-21906, 2023. https://doi.org/10.1007/s11042-020-09629-4
  18. J. Gleick, Chaos: Making a New Science. Soho, NY, USA: Open Road Media, 2011.
  19. D. M. Jimenez-Bravo, A.. L. Murciego, A. S. Mendes, H. S. San Blas, and J. Bajo, "Multi-object tracking in traffic environments: A systematic literature review," Neurocomputing, 2022.
  20. H. Kim, H. Kim, and E. Hwang, "Real-time shape tracking of facial landmarks," Multimedia Tools Appl., Vol. 79, pp. 15945-15963, 2020. https://doi.org/10.1007/s11042-018-6814-7
  21. P. Phillips, "Privacy Operating Characteristicfor Privacy Protection in Surveillance Applications," in Audio- and Video-Based Biometric Person Authentication, T. Kanade, A. Jain, and N. Ratha, Eds. Berlin/Heidelberg, Germany: Springer, 2005, pp. 869-878.
  22. J. Seo, S. Hwang, and Y.-H. Suh, "A Reversible Face De-Identification Method based on Robust Hashing," in Proc. Int. Conf. Consumer Electron., Algarve, Portugal, 14-16 April 2008.
  23. R. Gross, L. Sweeney, J. Cohn, F. de la Torre, and S. Baker, "Face De-identification," in Protecting Privacy in Video Surveillance, A. Senior, Ed. Berlin/Heidelberg, Germany: Springer, 2009.
  24. E. M. Newton, L. Sweeney, and B. Malin, "Preserving privacy by de-identifying face images," IEEE Trans. Knowl. Data Eng., Vol. 17, pp. 232-243, 2005. https://doi.org/10.1109/TKDE.2005.32
  25. B. Meden, R. C. Malli, S. Fabijan, H. K. Ekenel, V. Struc, and P. Peer, "Face de-identification with generative deep neural networks," IET Signal Process., Vol. 11, pp. 1046-1054, 2017. https://doi.org/10.1049/iet-spr.2017.0049
  26. Y.-L. Pan, M.-J. Haung, K.-T. Ding, J.-L. Wu, and J.-S. R. Jang, "K-Same-Siamese-GAN: K-Same Algorithm with Generative Adversarial Network for Facial Image De-identification with Hyperparameter Tuning and Mixed Precision Training," in Proc. 2019 16th IEEE Int. Conf. Adv. Video Signal Based Surveill. (AVSS), Taipei, Taiwan, 18-21 September 2019, pp. 1-8.
  27. Y. Jeong, J. Choi, S. Kim, Y. Ro, T.-H. Oh, D. Kim, H. Ha, and S. Yoon, "FICGAN: Facial Identity Controllable GAN for De-identification," arXiv preprint arXiv:2110.00740, 2021.
  28. M. Yamac, M. Ahishali, N. Passalis, J. Raitoharju, B. Sankur, and M. Gabbouj, "Reversible Privacy Preservation using Multi-level Encryption and Compressive Sensing," in Proc. 27th Eur. Signal Process. Conf., A Coruna, Spain, 2-6 September 2019.
  29. X. Gu, W. Luo, M. S. Ryoo, and Y. J. Lee, "Password-conditioned anonymization and deanonymization with face identity transformers," in Computer Vision-ECCV 2020: 16th European Conference, Glasgow, UK, August 23-28, 2020, Proceedings, Part XXIII 16, pp. 727-743, Springer International Publishing, 2020.
  30. W. Xia, Y. Zhang, Y. Yang, J.-H. Xue, B. Zhou, and M.-H. Yang, "GAN Inversion: A Survey," IEEE Trans. Pattern Anal. Mach. Intell., Vol. 45, No. 3, pp. 3121-3138, March 2023.
  31. J. Lin, Z. Chen, Y. Xia, S. Liu, T. Qin, and J. Luo, "Exploring Explicit Domain Supervision for Latent Space Disentanglement in Unpaired Image-to-Image Translation," IEEE Trans. Pattern Anal. Mach. Intell., Vol. 43, pp. 1254-1266, 2019.
  32. Y. Choi, M. Choi, M. Kim, J. W. Ha, S. Kim, and J. Choo, "StarGAN: Unified generative adversarial networks for multi-domain image-to-image translation," in Proc. IEEE Conf. Comput. Vision Pattern Recognit. (CVPR), Salt Lake City, UT, USA, 18-22 June 2018, pp. 8789-8797.
  33. P. Isola, J.-Y. Zhu, T. Zhou, and A. A. Efros, "Image-to-image translation with conditional adversarial networks," in Proc. IEEE Conf. Comput. Vision Pattern Recognit. (CVPR), Honolulu, HI, USA, 21- 26 July 2017, pp. 1125-1134.
  34. X. Cao, Y. Wei, F. Wen, and J. Sun, "Face alignment by explicit shape regression," in Proc. IEEE Conf. Comput. Vision Pattern Recognit. (CVPR), Providence, RI, USA, 16-21 June 2012, pp. 2887-2894.