Secure Third Party Data Clustering Using $$\varPhi $$ Data: Multi-User Order Preserving Encryption and Super Secure Chain Distance Matrices (Best Technical Paper)-Reference-Cited by-同舟云学术

Secure Third Party Data Clustering Using $$\varPhi $$ Data: Multi-User Order Preserving Encryption and Super Secure Chain Distance Matrices (Best Technical Paper)

Published:2018 Issue: Volume: Page:3-17
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
Short-container-title:

Author:

Almutairi Nawal,Coenen Frans,Dures Keith

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-04191-5_1

Reference18 articles.

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2. Agrawal, R., Srikant, R.: Privacy-preserving data mining. SIGMOD Rec. 29(2), 439–450 (2000)

3. Anikin, I.V., Gazimov, R.M.: Privacy preserving DBSCAN clustering algorithm for vertically partitioned data in distributed systems. In: IEEE International Siberian Conference on Control and Communications, pp. 1–4. IEEE (2017)

4. Bhaduri, K., Stefanski, M.D., Srivastava, A.N.: Privacy-preserving outlier detection through random nonlinear data distortion. IEEE Trans. Syst. Man Cybern. Part B (Cybern.) 41(1), 260–272 (2011)

5. Cachin, C.: Efficient private bidding and auctions with an oblivious third party. In: Proceedings of the 6th ACM Conference on Computer and Communications Security, pp. 120–127. ACM (1999)

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