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Project Title

Secure Storage Auditing with Efficient Key Updates for Cognitive Industrial IoT Environment


Cognitive computing over big data brings more development opportunities for enterprises and organizations in industrial informatics, and can make better decisions for them when they face data security challenges. To satisfy the requirement of real-time data storage in industrial Internet of things (IoT), the remote unconstrained storage cloud is usually used to store the generated big data. However, the characteristic of semi-trust of the cloud service provider (CSP) determines that the data owners will worry about whether the data stored in cloud computing has been corrupted. In this paper, a secure storage auditing is proposed, which supports efficient key updates and can be well used in cognitive industrial IoT environment. Moreover, the proposed basic auditing can be extended to support batch auditing that is suitable for multiple end devices to audit their data blocks simultaneously in practice.

Branch: CSE     Domain: Cloud Computing

Developed In: Java