Adaptive Multi-keyword Ranked Search Over Encrypted Cloud Data
To preserve data privacy and integrity, sensitive data has to be encrypted before outsourcing to the cloud server. However, this makes keyword search based on plaintext queries obsolete. Therefore, supporting efficient keyword based ranked searches over encrypted data became an open challenge. In recent years, several multi-keyword ranked search schemes have been proposed in trying to solve the posed challenge. However, most recently proposed schemes don’t address the issues regarding dynamics in the keyword dictionary. In this paper, we propose a novel scheme called A-MRSE that addresses and solves these issues. We introduce new algorithms to be used by data owners each time they make modifications that affects the size of the keyword dictionary. We conduct multiple experiments to demonstrate the effectiveness of our newly proposed scheme, and the results illustrates that the performance of A-MRSE scheme is much better that previously proposed schemes.
KeywordsCloud computing Searchable encryption Multi-keyword query Ranked search Encrypted data
This work is supported by National Natural Science Foundation of China under grants 61173170, 61300222, 61433006 and U1401258, Innovation Fund of Huazhong University of Science and Technology under grants 2015TS069 and 2015TS071, and Science and Technology Support Program of Hubei Province under grant 2014BCH270 and 2015AAA013, and Science and Technology Program of Guangdong Province under grant 2014B010111007.
- 1.Cao, N., Wang, C., Li, M., Ren, K., Lou, W.: Privacy-preserving multi-keyword ranked search over encrypted cloud data. In: Proceedings of INFOCOM, pp. 829–837. IEEE (2011)Google Scholar
- 2.Song D.X., Wanger, D., Perrig, A.: Practical techniques for searches on encrypted data. In: 2000 IEEE Symposium on Security and Privacy, pp. 44–55. IEEE (2000)Google Scholar
- 4.Wang, C., Cao, N., Li, J., Ren, K., Lou, W.: Secure ranked keyword search over encrypted cloud data. In: Proceedings of IEEE 30th International Conference in Distributed Computing Systems (ICDCS), pp. 253–262. IEEE (2010)Google Scholar
- 5.Xu, Z., Kang, W., Li, R., Yow, K., Xu, C.: Efficient multi-keyword ranked query on encrypted data in the cloud. In: The 18th International Conference on Parallel and Distributed Systems (ICPADS), pp. 244–251. IEEE (2012)Google Scholar
- 8.Wong, W.K., Cheung, D.W., Kao, B., Mamoulis, N.: Secure kNN computation on encrypted databases. In: Proceedings of the 2009 ACM SIGMOD International Conference on Management of Data, pp. 139–152. ACM (2009)Google Scholar
- 9.Cohen W.W.: Enron Email Dataset. http://www.cs.cmu.edu/~enron
- 10.Hicklin, J., Moler, C., Webb, P., Boisvert, R.F., Miller B., Pozo, R., Remington, K.: JAMA: Java Matrix Package. http://www.math.nist.gov/javanumerics/jama/
- 11.Mather, T., Kumaraswamy, S., Latif, S.: Cloud Security and Privacy: an Enterprise Perspective on Risks and Compliance. O’Reilly Media Inc., Sebastopol (2009)Google Scholar
- 15.Li, J., Wang, Q., Wang, C., Kao, N., Ren, K., Lou, W.: Fuzzy keyword search over encrypted data in cloud computing. In: Proceedings of INFOCOM, pp. 1–5. IEEE (2010)Google Scholar
- 16.Tang, H., Liu, F.M., Shen, G., Jin, Y., Guo, C.: UniDrive: synergize multiple consumer cloud storage services. In: ACM/USENIX/IFIP Middleware, Vancouver, Canada (2015)Google Scholar