Algebraic Signature-Based Public Data Integrity Batch Verification for Cloud-IoT

With the rapid development of Internet of Things, the related data are growing explosively. However, IoT devices have limited storage and computing capabilities so that they cannot deal with massive data storage and computing locally. The integration of IoT and cloud is regarded as an effective solution to the above issue, i.e., IoT devices outsource collected data to cloud to enjoy powerful storage and computing resources. Because the data stored in cloud are out of the control of IoT users, some security risks need to be addressed in advance. In this article, we propose a public data integrity verification scheme, called AIVCI, to check the data integrity for Cloud-IoT scenarios. First, based on algebraic signature and homomorphic hash function, AIVCI can efficiently complete data auditing. Second, AIVCI adopts blind technology to prevent the privacy leakage of IoT data and further protect the privacy of IoT users. Third, batch auditing is implemented to improve auditing efficiency and meet realistic demands for Cloud-IoT scenarios. And a new data structure named Improved Divide and Conquer Table (ID & CT) is designed to realize efficient data dynamics. Finally, the security and performance analyses demonstrate that AIVCI is more secure and efficient.

Automated summary

With the rapid development of Internet of Things, the integration of IoT and cloud is considered an effective solution to the limited storage and computing capabilities of IoT devices. However, the security risks of outsourced data stored in the cloud need to be addressed. This article proposes a public data integrity verification scheme, AIVCI, that efficiently checks data integrity, protects privacy, and improves auditing efficiency in Cloud-IoT scenarios.