참고문헌
- T. Root et al, Fingerprints of global warming on wild animals and plants, Nature 421 (2003), no. 6918, 57-60. https://doi.org/10.1038/nature01333
- Y. Zheng, D. K. Pal, and M. Savvides, Ring loss: Convex feature normalization for face recognition, in Proc. IEEE Conf. Comput. Vis. Pattern Recogn., Salt Lake Sity, Canada, June. 2018, pp. 5089-5097.
- M. Mottalli, M. Mejail, and J. Jacobo-Berlles, Flexible image segmentation and quality assessment for real-time iris recognition, in Proc. IEEE Int. Conf. Image Process. Cairo, Eqypt, Nov. 2010, pp. 1941-1944.
- L. E. Ali, J. Luo, and J. Ma, Iris recognition from distant images based on multiple feature descriptors and classifiers, in Proc. IEEE Int. Conf. Signal Process., Chengdu, China, Nov. 2016, pp. 1357-1362.
- K. Wang and K. Ajay, Cross-spectral iris recognition using cnn and supervised discrete hashing, Pattern Recogn. 86 (2019), 85-98. https://doi.org/10.1016/j.patcog.2018.08.010
- Z. Zhang et al, Bilateral privacy-preserving utility maximization protocol in database-driven cognitive radio networks, IEEE Trans. Depend. Secure Comput. (preprint), https://doi.org/10.1109/TDSC.2017.2781248.
- J. Fridrich, Image encryption based on chaotic maps, in Proc. IEEE Int. Conf. Syst. Man, Cybernetics, Orlando, FL, USA, Oct. 1997, pp. 1105-1110.
- J. Fridrich, Symmetric ciphers based on two-dimensional chaotic maps, Int. J. Bifurcat. Chaos 8 (1998), no. 6, 1259-1284. https://doi.org/10.1142/S021812749800098X
- K. Simoens et al, A framework for analyzing template security and privacy in biometric authentication systems, IEEE Trans. Inf. Forensics Secur. 7 (2012), no. 2, 833-841. https://doi.org/10.1109/TIFS.2012.2184092
- W. A. A. Torres, N. Bhattacharjee, and B. Srinivasan, Effectiveness of fully homomorphic encryption to preserve the privacy of biometric data, in Proc. Int. Conf. Inf. Integ. Web-based Applicat. Serv., Hanoi, Viet Nam, Dec. 2014, pp. 152-158.
- J. Bringer et al, Faster secure computation for biometric identification using filtering, in Proc. Int. Conf. Biometrics, New Delhi, India. 2013, pp. 257-264.
- B. Hayes, Cloud computing, Web Sci. 51 (2008), no. 7, 9-11.
- J. P. Hespanha, P. Naghshtabrizi, and Y. Xu, A survey of recent results in networked control systems, Proc. IEEE 95 (2007), no. 1, 138-162. https://doi.org/10.1109/JPROC.2006.887288
- H. Zhang et al, Privacy and performance trade-off in cyber-physical systems, IEEE Netw. 30 (2016), no. 2, 62-66. https://doi.org/10.1109/MNET.2016.7437026
- N. Srichumroenrattana, R. Lipikorn, and C. Lursinsap, Stereoscopic face reconstruction from a single 2-dimensional face image using orthogonality of normal surface and y-ratio, Int. J. Pattern Recognit. Artif. Intell. 30 (2016), no. 2, 1-27.
- B. Benjamin et al, DP-finder: Finding differential privacy violations by sampling and optimization, in Proc. ACM SIGSAC Conf. Comput. Commun. Secur., Toronto, Canada, Oct. 2018, pp. 508-524.
- A. Martin et al, Deep learning with differential privacy, in Proc. ACM SIGSAC Conf. Comput. Commun. Secur., Vienna, Austria, Oct. 2016, pp. 308-318.
- C. Thee et al, MVG mechanism: differential privacy under matrixvalued query, in Proc. ACM SIGSAC Conf. Comput. Commun. Secur., Toronto, Canada, Oct. 2018, pp. 1-17.
- A. Bhowmick et al, Protection against reconstruction and its applications in private federated learning, Mach. Learn. 1812 (2018), 1-45.
- R. Venkatesan, S.-M. Koon, and M. Jakubowski, Robust image hashing, in Proc. ACM SIGSAC Conf. Comput. Commun. Secur., 2000, pp. 664-666.
- T. Kalker, J. Haitsma, and J. Oostveen, Issues with digital watermarking and perceptual hashing, in Proc. Int. Symp. Converg. IT Commun., Denver, CO, USA, 2001, pp. 189-197.
- J. Fridrich and M. Goljan, Robust hash functions for digital watermarking, in Proc. Int. Conf. Inf. Technol. Coding Comput., Las Vegas, NV, USA, Mar. 2000, pp. 1-6.
- L. Chun-Shien et al, Robust mesh-based hashing for copy detection and tracing of images, in Proc. IEEE Int. Conf. Multimedia Expo, Taipei, Taiwan, June 2004, pp. 731-734.
- S. Kozat, R. Venkatesan, and M. K. Mihcak, Robust perceptual image hashing via matrix invariants, in Proc. Int. Conf. Image Process., Singapore, Oct. 2004, pp. 3443-3446.
- Z. Tang et al, Robust image hashing using ring-based entropies, Signal Process. 93 (2013), no. 7, 2061-2069. https://doi.org/10.1016/j.sigpro.2013.01.008
- H. Wei, J. X. Yu, and C. Lu, String similarity search: a hashbased approach, IEEE Trans. Knowl. Data Eng. 30 (2018), no. 1, 170-184. https://doi.org/10.1109/TKDE.2017.2756932
- Z. Liu et al, Contextual hashing for large-scale image search, IEEE Trans. Image Process. 23 (2014), no. 4, 1606-1614. https://doi.org/10.1109/TIP.2014.2305072
- M. De Marsico et al, Firme: face and iris recognition for mobile engagement, Image Vis. Comput. 32 (2014), no. 12, 1161-1172. https://doi.org/10.1016/j.imavis.2013.12.014
- W. Boles, A security system based on human iris identification using wavelet transform, in Proc. Int. Conf. Convent. Knowl. Based Intell. Electron. Syst., Adelaide, Australia, May 1997, pp. 533-541.
- C. Dwork, Differential privacy, in Proc. Int. Colloquium Automata Lang. Program., Venice, Italy, July 2006, pp. 1-12.
- J. Soria-Comas et al, Individual differential privacy: a utilitypreserving formulation of differential privacy guarantees, IEEE Trans. Inf. Forensics Secur. 12 (2017), no. 6, 1418-1429. https://doi.org/10.1109/TIFS.2017.2663337
- S. Goryczka and X. Li, A comprehensive comparison of multiparty secure additions with differential privacy, IEEE Trans. Dependable Secure Comput. 14 (2017), no. 5, 463-477. https://doi.org/10.1109/TDSC.2015.2484326
- F. Liu, Generalized gaussian mechanism for differential privacy, IEEE Trans. Knowl. Data Eng. 31 (2019), no. 4, 747-756. https://doi.org/10.1109/TKDE.2018.2845388
- Y. Feng et al, Visual tracking via multi-experts combined with average hash model, Proc. Asian Conf. pattern recognition. (2016), 331-335.
- X. Niu and Y. Jiao, An overview of perceptual hashing, Acta Electronica Sinica 36 (2008), no. 7, 1405-1411. https://doi.org/10.3321/j.issn:0372-2112.2008.07.029
- G. Vrcek and P. Peer, Iris-based human verification system: a research prototype, in Proc. Int. Conf. Syst., Chalkida, Greece, June 2009, pp. 1-4.