Ranked Query Support in Untrusted Cloud without Reveal Sensitive Data
Main Article Content
Abstract
Now-a-days Cloud computing is become more popular as cloud infrastructure for storing the data. Data owners are stored their data in public cloud for the flexibility and cost-preserving. In order to providing data privacy, Clouds allow users to store data and access can be made anywhere, any time by using any device. Highly sensitive information such as business documents, medical records and personal information may be stored in a cloud. Security and privacy are thus very important issues in cloud computing. To keep user data confidential from an untrusted Cloud Service Provider and third parties, a natural way is encryption. The data decryption key should be disclosed only to users who have been authorized. Users can search their files using keywords in the cloud. In existing literature many schemes have been proposed. In this paper, a new technique is described: Ranked Query support in Untrusted Cloud without Reveal Sensitive Data. Which performs operations on encrypted data which will provide results without decrypting that data? It provides privacy for user querying patterns and user data. It allows Cloud Service Providers to perform operations on the encrypted data. The Cloud Service Provider is unaware of the files and keywords stored in the cloud. Ranking is used for efficient and fast retrieval of the desired files. Ranks will be assigned to files based on the frequency of access of the files.
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
IJCERT Policy:
The published work presented in this paper is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. This means that the content of this paper can be shared, copied, and redistributed in any medium or format, as long as the original author is properly attributed. Additionally, any derivative works based on this paper must also be licensed under the same terms. This licensing agreement allows for broad dissemination and use of the work while maintaining the author's rights and recognition.
By submitting this paper to IJCERT, the author(s) agree to these licensing terms and confirm that the work is original and does not infringe on any third-party copyright or intellectual property rights.
References
Cao, N., Wang, C., Li, M., Ren, K., & Lou, W. (2014). “Privacypreserving multi-keyword ranked search over encrypted cloud data.”Parallel and Distributed Systems, IEEE Transactions on, 25(1), 222-233.
Wei, L., & Reiter, M. K. (2011). “Third-party DFA evaluation on encrypted files”. Tech. Rep. TR11-005, Department of Computer Science, University of North Carolina at Chapel Hill.
Xu, H., Guo, S., & Chen, K. (2012). “Building confidential and efficient query services in the cloud with RASP data perturbation”. arXiv preprint arXiv:1212.0610.
Wang, C., Cao, N., Li, J., Ren, K., & Lou, W. (2010, June). “Secure ranked keyword search over encrypted cloud data.” In Distributed Computing Systems (ICDCS), 2010 IEEE 30th International Conference on (pp. 253-262). IEEE.
Liu, Q., Tan, C. C., & Wang, G. (2014). “Towards Differential Query Services in Cost-Efficient Clouds.” Parallel and Distributed Systems, IEEE Transactions on,25(6), 1648-1658.
Hua, Y., Xiao, B., Veeravalli, B., & Feng, D. (2012). “Localitysensitive Bloom filter for approximate membership query.” Computers, IEEE Transactions on,61(6), 817-830.
Liu, Q., Tan, C. C., Wu, J., & Wang, G. (2012, March). “Efficient information retrieval for ranked queries in cost-effective cloud environments.” In INFOCOM, 2012 Proceedings IEEE (pp. 2581- 2585). IEEE.
Cabarcos, P. A., Mendoza, F. A., Guerrero, R. S., Lopez, A. M., & Diaz-Sanchez, D. (2012). Telematic Eng. Dept., Carlos III Univ. of Madrid, Leganes, Spain. Consumer Electronics, IEEE Transactions on, 58(4), 1425-1433.
Fu, Z., Sun, X., Linge, N., & Zhou, L. (2014). “Achieving effective cloud search services: multi-keyword ranked search over encrypted cloud data supporting synonym query.” Consumer Electronics, IEEE Transactions on, 60(1), 164-172.