Attribute based hybrid encryption policy for encrypting the cloud data

Shweta , Dr Jayashree Agarkhed

Random key generation, Dual encryption, time seal, Malware injection attack.

In the cloud, for keeping data confidential and achieving access control, the data owners could adopt attribute-based encryption to encrypt the stored data. Users with limited computing power are more likely to delegate the original of the decryption task to the cloud servers to reduce the cost computing. As a result, attribute-based encryption with delegation emerges. Still, there are warning and questions remaining in the previous relevant works. For instance, during the delegation, the cloud servers could damage or replace the delegated ciphertext and respond a forged computing result with malicious intent. They may also cheat the authorized users by responding them that they are ineligible for the purpose of cost saving. Furthermore, during the encryption, the access policies may not be flexible enough. Since policy for general circuits enables to achieve the strongest form of access control, a construction for realizing ciphertext-policy attribute-based hybrid encryption with verifiable delegation in the cloud has been considered in this work. In such a system, combined with verifiable computation and encrypt-then-mac mechanism, the data confidentiality, the fine-grained access control and the defects of the delegated computing results are well guaranteed at the same time. Besides, our scheme achieves security against chosen-plaintext attacks under k-multilinear Decisional & Diffie-Hellman assumption. Moreover, an extensive simulation campaign confirms the feasibility and efficiency of the proposed solution.

"Attribute based hybrid encryption policy for encrypting the cloud data ", IJRTI - International Journal for Research Trends and Innovation (www.IJRTI.org), ISSN:2456-3315, Vol.2, Issue 7, page no.115 - 118, July-2017, Available :https://ijrti.org/papers/IJRTI1707019.pdf

Volume 2 Issue 7, July-2017

Pages : 115 - 118

Paper Reg. ID: IJRTI_170428

Published Paper Id: IJRTI1707019

Downloads: 205,618

Research Area: Engineering

Country: Gulbarga, Karnataka, India

Published Paper PDF: https://ijrti.org/papers/IJRTI1707019

Published Paper URL: https://ijrti.org/viewpaperforall?paper=IJRTI1707019

ISSN: 2456-3315 | IMPACT FACTOR: 10.57 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 10.57 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

UGC CARE Approved — Transparent Peer-reviewed journal aligned with UGC’s 2025 suggestive parameters.

Publisher: IJRTI (JW Publication)