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

Yanping Li, Zirui Li, Bo Yang, Yong Ding

2023IEEE Transactions on Cloud Computing33 citationsDOI

Abstract

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 paper, we propose a public data integrity verification scheme, called AIVCI, to check the data integrity for Cloud-IoT scenarios. Firstly, based on algebraic signature and homomorphic hash function, AIVCI can efficiently complete data auditing. Secondly, AIVCI adopts blind technology to prevent the privacy leakage of IoT data and further protect the privacy of IoT users. Thirdly, 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 analysis demonstrates that AIVCI is more secure and efficient.

Topics & Concepts

Computer scienceCloud computingData integrityHomomorphic encryptionComputer securityCloud storageInformation privacyOutsourcingHash functionSecurity analysisDistributed computingEncryptionOperating systemLawPolitical scienceCloud Data Security SolutionsCryptography and Data SecurityBlockchain Technology Applications and Security
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