k-means clustering and kNN classification based on negative databases

Applied Soft Computing - Tập 110 - Trang 107732 - 2021
Dongdong Zhao1, Xiaoyi Hu1, Shengwu Xiong1, Jing Tian1, Jianwen Xiang1, Jing Zhou2, Huanhuan Li3
1Hubei Key Laboratory of Transportation Internet of Things, School of Computer Science and Technology, Wuhan University of Technology, Wuhan, Hubei, China
2Operation Software and Simulation Institute, Dalian Naval Academy, China
3School of Computer Science, China University of Geosciences, Wuhan, China

Tài liệu tham khảo

Rehioui, 2019, New clustering algorithms for twitter sentiment analysis, IEEE Syst. J., 14, 530, 10.1109/JSYST.2019.2912759 Zhang, 2020, Cost-sensitive KNN classification, Neurocomputing, 391, 234, 10.1016/j.neucom.2018.11.101 Yang, 2019, A feature-reduction multi-view k-means clustering algorithm, IEEE Access, 7, 114472, 10.1109/ACCESS.2019.2934179 J. Vaidya, C. Clifton, Privacy-preserving k-means clustering over vertically partitioned data, in: Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD’03, 2003, pp. 206–215. G. Jagannathan, R.N. Wright, Privacy-preserving distributed k-means clustering over arbitrarily partitioned data, in: Proceedings of the Eleventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD’05, 2005, pp. 593–599. M.C. Doganay, T.B. Pedersen, Y. Saygin, E. Savas, A. Levi, Distributed privacy preserving k-means clustering with additive secret sharing, in: Proceedings of the 2008 International Workshop on Privacy and Anonymity in Information Society, PAIS’08, 2008, pp. 3–11. Liu, 2014, Privacy of outsourced k-means clustering, 123 Meskine, 2012, Privacy preserving k-means clustering: a survey research., Int. Arab J. Inf. Technol., 9, 194 F. Esponda, Everything that is not important: Negative databases [Research Frontier], IEEE Comput. Intell. Mag. 2008, 3 (2) 60–63. Esponda, 2007, Protecting data privacy through hard-to-reverse negative databases, Int. J. Inf. Secur., 6, 403, 10.1007/s10207-007-0030-1 Esponda, 2004 Forrest, 1994, Self-nonself discrimination in a computer, 202 Liu, 2014, The p-hidden algorithm: hiding single databases more deeply, Immune Comput., 2, 43 Zhao, 2015, A fine-grained algorithm for generating hard-to-reverse negative databases, 1 Liu, 2013, Classifying and clustering in negative databases, Front. Comput. Sci., 7, 864, 10.1007/s11704-013-2318-9 Hu, 2018, Privacy-preserving K-means clustering upon negative databases, vol. 11304, 191 Liao, 2019, Privacy-protected kNN classification algorithm based on negative database, 61 Zhao, 2018, Negative iris recognition, IEEE Trans. Dependable Secure Comput., 15, 112, 10.1109/TDSC.2015.2507133 D. Zhao, X. Hu, S. Xiong, J. Tian, J. Xiang, J. Zhou, H. Li, A fine-grained privacy-preserving k-means clustering algorithm upon negative databases, in: The 2019 IEEE Symposium Series on Computational Intelligence (SSCI 2019), IComputation’19, 2019, pp. 1945–1951. Jha, 2005, Privacy preserving clustering, 397 Bunn, 2007, Secure two-party k-means clustering, 486 Zhu, 2020, Privacy-preserving k-means clustering with local synchronization in peer-to-peer networks, Peer-To-Peer Netw. Appl., 13, 2272, 10.1007/s12083-020-00881-x Xing, 2017, Mutual privacy preserving k-means clustering in social participatory sensing, IEEE Trans. Ind. Inf., 13, 2066, 10.1109/TII.2017.2695487 Mukherjee, 2006, A privacy-preserving technique for Euclidean distance-based mining algorithms using Fourier-related transforms, VLDB J., 15, 293, 10.1007/s00778-006-0010-5 Dhiraj, 2009, Privacy preservation in k-means clustering by cluster rotation, 1 Ren, 2017, DPLK-Means: A novel differential privacy k-means mechanism, 133 V. Schellekens, A. Chatalic, F. Houssiau, Y.D. Montjoye, L. Jacques, R. Gribonval, Differentially private compressive k-means, in: ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP, 2019, pp. 7933–7937. Z. Lu, H. Shen, A convergent differentially private k-means clustering algorithm, in: Pacific-Asia Conference on Knowledge Discovery and Data Mining, 2019, pp. 612–624. U. Stemmer, Locally private k-means clustering, in: Proceedings of the 2020 ACM-SIAM Symposium on Discrete Algorithms, 2020, pp. 548–559. Xia, 2020, Distributed k-Means clustering guaranteeing local differential privacy, Comput. Secur., 90, 10.1016/j.cose.2019.101699 Lin, 2020, A reversible privacy-preserving clustering technique based on k-means algorithm, Appl. Soft Comput., 87, 10.1016/j.asoc.2019.105995 Esponda, 2007 Zhan, 2005, Privacy preserving k-nearest neighbor classification, Int. J. Netw. Secur., 1, 46 Wong, 2009, Secure kNN computation on encrypted databases, 139 Wu, 2019, Privacy preserving k-nearest neighbor classification over encrypted database in outsourced cloud environments, World Wide Web, 22, 101, 10.1007/s11280-018-0539-4 Liu, 2019, Toward highly secure yet efficient kNN classification scheme on outsourced cloud data, IEEE Internet Things J., 6, 9841, 10.1109/JIOT.2019.2932444 Lian, 2020, Efficient and secure k-nearest neighbor query on outsourced data, Peer-To-Peer Netw. Appl., 13, 2324, 10.1007/s12083-020-00909-2 Sun, 2020, An efficient secure k nearest neighbor classification protocol with high-dimensional features, Int. J. Intell. Syst., 35, 1791, 10.1002/int.22272 Haque, 2020, Privacy-preserving k-nearest neighbors training over blockchain-based encrypted health data, Electronics, 9, 2096, 10.3390/electronics9122096 Gorai, 2011, Employing bloom filters for privacy preserving distributed collaborative kNN classification, 495 Chen, 2005 Jalla, 2019, Privacy-preserving kNN classification using vector operations, 655 Qi, 2008, Efficient privacy-preserving k-nearest neighbor search, 311 Shaneck, 2009, Privacy preserving nearest neighbor search, 247 Songhori, 2015, Compacting privacy-preserving k-nearest neighbor search using logic synthesis, 1 Esponda, 2008, Hiding a needle in a haystack using negative databases, 15 Luo, 2019, Authentication by encrypted negative password, IEEE Trans. Inf. Forensics Secur., 14, 114, 10.1109/TIFS.2018.2844854 Luo, 2018, Three branches of negative representation of information: A survey, IEEE Trans. Emerg. Top. Comput. Intell., 2, 411, 10.1109/TETCI.2018.2829907 Jia, 2005, Generating hard satisfiable formulas by hiding solutions deceptively, 384 Pendigit dataset, 2020 Davies, 1979, A cluster separation measure, IEEE Trans. Pattern Anal. Mach. Intell., PAMI-1, 224, 10.1109/TPAMI.1979.4766909