Youwen Zhu
ABSTRACT
In cloud computing, secure analysis on outsourced encrypted data is a significant topic. As a frequently used query for online applications, secure k-nearest neighbors (k-NN) computation on encrypted cloud data has received much attention, and several solutions for it have been put forward. However, most existing schemes assume the query users are fully trusted and all query users share the total key which is used to encrypt and decrypt data owner's outsourced data. It is constitutionally not feasible in lots of real-world applications. In this paper, we propose a novel secure and efficient scheme for k-NN query on encrypted cloud data in which the key of data owner to encrypt and decrypt ousourced data will not be completely disclosed to any query user. Therefore, our scheme can efficiently support the secure k-NN query on encrypted cloud data even when query users are not trustworthy enough.
- S. Kamara and K. Lauter. Cryptographic cloud storage. In Financial Cryptography: Workshop on Real-Life Cryptographic Protocols and Standardization, LNCS 6054, pages 136--149, 2010. Google Scholar
Digital Library
- W.K. Wong, D.W. Cheung, B. Kao, and N. Mamoulis. Secure knn computation on encrypted databases. In Proceedings of the 35th SIGMOD, pages 139--152, 2009. Google ScholarDigital Library
- M.D. Singh, P.R. Krishna, and A. Saxena. A cryptography based privacy preserving solution to mine cloud data. In the 3rd Annual ACM Bangalore Conference, 2010. Google ScholarDigital Library
- H. Hu, J. Xu, C. Ren, and B. Choi. Processing private queries over untrusted data cloud through privacy homomorphism. In IEEE 27th International Conference on Data Engineering (ICDE), pages 601--612, 2011. Google ScholarDigital Library
- B. Hore, S. Mehrotra, M. Canim, and M. Kantarcioglu. Secure multidimensional range queries over outsourced data. The VLDB Journal, 21(3):333--358, 2012. Google ScholarDigital Library
- C. Wang, K. Ren, S. Yu, and K.M.R. Urs. Achieving usable and privacy-assured similarity search over outsourced cloud data. In Proceedings of IEEE INFOCOM, pages 451--459, 2012.Google ScholarCross Ref
- C. Wang, N. Cao, K. Ren, and W. Lou. Enabling secure and efficient ranked keyword search over outsourced cloud data. IEEE Transactions on Parallel and Distributed Systems, 23(8):1467--1479, 2012. Google ScholarDigital Library
- C. Wang, N. Cao, J. Li, K. Ren, and W. Lou. Secure ranked keyword search over encrypted cloud data. In 30th IEEE International Conference on Distributed Computing Systems (ICDCS), pages 253--262, 2010. Google ScholarDigital Library
- Y. Qi and M.J. Atallah. Efficient privacy-preserving k-nearest neighbor search. In the 28th IEEE International Conference on Distributed Computing Systems(ICDCS), pages 311--319, 2008. Google ScholarDigital Library
- M. Shaneck, Y. Kim, and V. Kumar. Privacy preserving nearest neighbor search. In IEEE ICDM Workshops, pages 541--545, 2006. Google ScholarDigital Library
- K. Chen and L. Liu. Privacy preserving data classification with rotation perturbation. In 5th IEEE International Conference on Data Mining (ICDM), 2005. Google ScholarDigital Library
- S.R.M. Oliveira and O.R. Zaiane. Privacy preserving clustering by data transformation. In Proc. of the 18th Brazilian Symposium on Databases, pages 304--318, 2003.Google Scholar
- N. Cao, C. Wang, M. Li, K. Ren, and W. Lou. Privacy-preserving multi-keyword ranked search over encrypted cloud data. In Proceedings of IEEE International Conference on Computer Communications (INFOCOM), pages 829--837, 2011.Google ScholarCross Ref
- N. Cao, Z. Yang, C. Wang, K. Ren, and W. Lou. Privacy-preserving query over encrypted graph-structured data in cloud computing. In 31st International Conference on Distributed Computing Systems (ICDCS),, pages 393--402. IEEE, 2011. Google ScholarDigital Library
- M. Li, S. Yu, W. Lou, and Y.T. Hou. Toward privacy-assured cloud data services with flexible search functionalities. In IEEE ICDCS Workshops, pages 466--470, 2012. Google ScholarDigital Library
- A. C. Yao. Protocols for secure computations. In the 23rd Annual IEEE Symposium on Foundations of Computer Science, pages 160--164, 1982. Google ScholarDigital Library
- O. Goldreich. Foundations of Cryptography: Volume II, Basic Applications. Cambridge: Cambridge University Press, 2004. Google ScholarDigital Library
- A.C. Yao. How to generate and exchange secrets. In 27th Annual Symposium on Foundations of Computer Science (FOCS), pages 162--167. IEEE, 1986. Google ScholarDigital Library
- O. Goldreich, S. Micali, and A. Wigderson. How to play any mental game, or a completeness theorem for protocols with an honest majority. In Proc. of the 19th Annual ACM Symposium on Theory of Computing (STOC),, pages 218--229. ACM Press, 1987. Google ScholarDigital Library
- T. Pedersen. Non-interactive and information-theoretic secure verifiable secret sharing. In CRYPTO, pages 129--140. Springer, 1991. Google ScholarDigital Library
- I. Damgård, M. Fitzi, E. Kiltz, J. Nielsen, and T. Toft. Unconditionally secure constant-rounds multi-party computation for equality, comparison, bits and exponentiation. pages 285--304, 2006. Google ScholarDigital Library
- P. Paillier. Public-key cryptosystems based on composite degree residuosity classes. In EUROCRYPT, pages 223--238. LNCS 1592, Springer, 1999. Google ScholarDigital Library
- C.C. Aggarwal and S.Y. Philip. Privacy-preserving data mining: models and algorithms, volume 34. Springer, 2008. Google ScholarDigital Library
- K. Chen, G. Sun, and L. Liu. Towards attack-resilient geometric data perturbation. In SIAM data mining conference, 2007.Google Scholar
- K. Liu, C. Giannella, and H. Kargupta. An attacker?s view of distance preserving maps for privacy preserving data mining. In 10th European Conference on Principles and Practice of Knowledge Discovery in Databases, pages 297--308, 2006. Google ScholarDigital Library
- K. Liu, C. Giannella, and H. Kargupta. A survey of attack techniques on privacy-preserving data perturbation methods. In Privacy-Preserving Data Mining, pages 359--381. Springer, 2008.Google Scholar
Index Terms
- Secure k-NN computation on encrypted cloud data without sharing key with query users
Recommendations
Secure k-NN Query on Encrypted Cloud Data with Limited Key-Disclosure and Offline Data Owner
PAKDD 2016: Proceedings, Part II, of the 20th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining - Volume 9652Recently, many schemes have been proposed to support k-nearest neighbors k-NN query on encrypted cloud data. However, existing approaches either assume query users are fully-trusted, or require data owner to be online all the time. Query users in fully-...
An efficient and secure data sharing framework using homomorphic encryption in the cloud
Cloud-I '12: Proceedings of the 1st International Workshop on Cloud IntelligenceDue to cost-efficiency and less hands-on management, data owners are outsourcing their data to the cloud which can provide access to the data as a service. However, by outsourcing their data to the cloud, the data owners lose control over their data as ...
Secure k-NN query on encrypted cloud database without key-sharing
In cloud computing, secure analysis on outsourced encrypted data is a significant topic. As a frequently used query for online applications, secure k-nearest neighbours k-NN computation on encrypted cloud data has received much attention, and several ...
Comments