A SYSTEMATIC AND COMPOSED BIG DATA ENTRY RESTRICTION SCHEME WITH ISOLATION-PRESERVING POLICY

Main Article Content

Abraham Rajan
Venkatesh Prasad

Abstract

: In modern world of technologies, each and every object like smart phones, computers connected to internet generates large amount of data. It becomes a very challenging issue for data to be stored in structured formats, specifically when it is stored to storages such as Cloud. It is also challenging that the privacy of data is maintained. We have an encryption technique known as Cipher text-policy attribute-based encryption (CP-ABE) which can be used by the users to encrypt their own data using attribute values which is defined over some access policies. If the attribute values of data consumers are matched with access policies of the data owners then such users are allowed to decrypt the data. In CPABE, we have access policies attached to the encrypted data in plain text formats which may contain some private information regarding the end-users. These methods will only partially conceal the private information while the attribute values are still exposed. In this paper, we propose data access control which also ensures privacy of the data owners and data consumers. And also we have bloom-filter which is used for attribute based decryption. It is used to assess whether the attribute is in the access policies defined by end-users. It can also find the exact location of the attribute if it is present in the access-policy. It has been assessed by many security analyst and execution performance evaluators that our proposed technique can prevent private information from any linear secret-sharing strategic access policies without engaging much overhead. In our project we provide two login constraints, one as data owner and the other as data consumer. The data owner uploads a file and generates a tag number for each file once the encryption is done. This will protect the attribute values such as file name from leaking. File name may contain some information regarding the attribute values which can be used by the intruders to decrypt the files. Therefore, by providing tag number it is able to protect privacy of the data owners.


Downloads

Download data is not yet available.

Article Details

Section
Articles

References

K. Bilal, S. U. Khan, L. Zhang, H. Li, K. Hayat, S. A. Madani, N. Min-Allah, L. Wang, D. Chen, M. Iqbal, C. Z. Xu, and A. Y.Zomaya, “Quantitative comparisons of the state of the art datacenter architectures, â€Concurrency and Computation: Practice and Experience, Vol. 25, No. 12, 2013, pp. 1771-1783. [2] K. Bilal, M. Manzano, S. U. Khan, E. Calle, K. Li, and A. Zomaya, “On the characterization of the structural robustness of data center networks, â€IEEE Transactions on Cloud Computing, Vol. 1, No. 1, 2013, pp. 64-77. [3] D. Boru, D. Kliazovich, F. Granelli, P. Bouvry, and A. Y. Zomaya,“Energy-efficient data replication in cloud computing datacenters,†In IEEE Globecom Workshops, 2013, pp. 446-451. . [4] Y. Deswarte, L. Blain, and J-C. Fabre, “Intrusion tolerance in distributed computing systems,†In Proceedings of IEEE Computer Society Symposium on Research in Security and Privacy, OaklandCA, pp. 110-121, 1991. [5] B. Grobauer, T.Walloschek, and E. Stocker, “Understanding cloud computing vulnerabilities, â€IEEE Security and Privacy, Vol.9, No. 2, 2011, pp. 50-57.