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2019 | OriginalPaper | Chapter

Consensus-Based Privacy-Preserving Algorithm

Authors : Heng Li, Fangfang Xu

Published in: Communications, Signal Processing, and Systems

Publisher: Springer Singapore

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Abstract

In this paper, we use secure multi-party computation to protect privacy. Based on consensus-based distributed support vector machines, we present a new consensus-based privacy-preserving algorithm to conduct secure multi-party computation. The proposed algorithm run in parallel at each iteration, which reduce the running time. Furthermore, what needed to be communicated at each iteration is only a coefficient vector, therefore privacy is protected to the uttermost. The algorithm is proved to be convergent globally. Numerical experiments demonstrate the feasibility and efficiency of the new algorithm.

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Lu, Y., Roychowdhury, V., Vandenberghe, L.: Distributed parallel support vector machines in strongly connected networks. IEEE Trans. Neural Netw. 19, 1167–1178 (2008)

Navia-Vazquez, A., Gutierrez-Gonzalez, D., Parrado-Hernandez, E., Navarro-Abellan, J.J.: Distributed support vector machines. IEEE Trans. Neural Netw. 17, 1091–1097 (2006)

Forero, P.A., Cano, A., Giannakis, G.B.: Consensus-based distributed support vector machines. J. Mach. Learn. Res. 11, 1663–1707 (2010)

Lindell, Y., Pinkas, B.: Secure multiparty computation for privacy-preserving data mining. J. Privacy Confidentiality 1, 59–98 (2009)

Zhang, Y., Zhong, S.: A privacy-preserving algorithm for distributed training of neural network ensembles. Neural Comput. Appl. 22, 269–282 (2013)

Wang, L., Shi, J.J., Chen, C., Zhong, S.: Privacy-preserving face detection based on linear and nonlinear kernels. In: Multimedia Tools and Applications, pp. 1–21 (2017)

Forero, P.A., Cano, A., Giannakis, G.B.: Consensus-based K-means algorithm for distributed learning using wireless sensor networks. In: Proceedings of Workshop on Sensors, Signal and Information Processing, Sedona, AZ, May 2008

Bertsekas, D.P., Tsitsiklis, J.N.: Parallel and Distributed Computation: Numerical Methods. Athena Scientific, Massachusetts (1997)

Asuncion, A., Newman, D.J.: Statlog training set. http://www.csie.ntu.edu.tw/cjlin/libsvmtools/datasets/

10.

Flouri, K., Beferull-Lozano, P., Tsakalides, P.: Training a support-vector machine-based classifier in distributed sensor networks. In: Proceedings of 14th European Signal Processing Conference, Florence, Italy, 4–8 September 2006

11.

Flouri, K., Beferull-Lozano, P., Tsakalides, P.: Distributed consensus algorithm for SVM training in wireless sensor networks. In: Proceedings of 16th European Signal Processing Conference, Laussane, Switzerland, 25–29 August 2008

12.

Bennati, S., Jonker, C.M.: PriMaL: a privacy-preserving machine learning method for event detection in distributed sensor networks (2017)

13.

Mangasarian, O.L., Wild, E.W., Fung, G.M.: Privacy-preserving classification of horizontally partitioned data via random kernels. In: Proceedings of the 2008 International Conference on Data Mining, vol. 2, pp. 473–479 (2008)

14.

Ruan, M., Wang, Y.: Secure and privacy-preserving average consensus (2017)

15.

Sagastizabal, C.A., Solodov, M.V.: Parallel variable distribution for constrained optimization. Comput. Optim. Appl. 22, 111–131 (2002)

16.

Ceccarello, M., Pietracaprina, A., Pucci, G., et al.: A practical parallel algorithm for diameter approximation of massive weighted graphs. In: IEEE International Parallel and Distributed Processing Symposium, pp. 12–21 (2016)

17.

Do, T.N., Nguyen, V.H., Poulet, F.: GPU-based parallel SVM algorithm. J. Front. Comput. Sci. Technol. 3, 368–377 (2009)

18.

Dai, Y.H., Fletcher, R.: New algorithms for singly linearly constrained quadratic programs subject to lower and upper bounds. Math. Program. 20, 403–421 (2006)

19.

Solodov, M.V.: New inexact parallel variable distributed algorithm. Comput. Optim. Appl. 7, 165–182 (1997)

20.

Zanni, L.: An improved gradient projection-based decomposition technique for support vector machines. CMS 3, 131–145 (2006)

21.

Huang, M., Chen, Y., Chen, B.W., et al.: A semi-supervised privacy-preserving clustering algorithm for healthcare. Peer-to-Peer Netw. Appl. 9, 864–875 (2016)

22.

Canetti, R.: Security and composition of multi-party cryptographic protocols. J. Cryptology 13, 143–202 (2000)

23.

Zhang, M.L., Han, M., Wang, Z.Z.: Inter-systems privacy-preserving recommendation algorithm based on security multi-party computation. J. Hebei Univ. Technol. (2012)

Title: Consensus-Based Privacy-Preserving Algorithm
Authors: Heng Li
Fangfang Xu
Publisher: Springer Singapore
Book: Communications, Signal Processing, and Systems
Print ISBN: 978-981-10-6570-5

Electronic ISBN: 978-981-10-6571-2

Copyright Year: 2019
DOI: https://doi.org/10.1007/978-981-10-6571-2_203