Secure and Efficient Data Integrity Based on Iris Features in Cloud Computing

Abstract

Cloud computing aids users to outsource their data in the cloud remotely to prevent them from burdens of local storage and maintenance. Users no longer have possession and control of these data. This property brings many new security challenges like unauthorised entities and correctness of stored data. In this paper, we focus on the problem of ensuring the integrity of data stored in the cloud. We propose a method which combines biometric and cryptography techniques in a cost-effective manner for data owners to gain trust in the cloud. We present efficient and secure integrity based on the XOR operation and iris feature extraction as the strong factors. This work gives the cloud user more confidence in detecting any block that has been changed. Additionally, our proposed scheme employs user's iris features to secure and integrate data in a manner difficult for any internal or external entity to take or compromise it. Extensive security and performance analysis show that our scheme is highly efficient and provably secure.