An integrity auditing scheme based on MHT for power equipment images stored in the cloud

doi:10.3969/j.issn.1000-5641.202091012

Abstract

Abstract: This paper proposes an integrity auditing scheme suitable for power equipment images stored in the cloud with the aim of addressing the risks of being attacked, tampered with, or lost. First, each image is cut into four image blocks, and then a Scale Invariant Feature Transform (SIFT) algorithm is used to extract features from the image blocks. The four image blocks for each image are subsequently used as a leaf node to construct a Merkle Hash Tree (MHT). Finally, access level bits and update status bits are added to the nodes of the tree. Theoretical analysis and experimental results show that the proposed image integrity auditing scheme has lower computational overhead and higher audit efficiency compared to existing approaches; hence, the scheme can accurately locate the incomplete area of an image and is suitable for auditing integrity of power equipment images in a cloud storage environment.

Key words: power equipment image, cloud storage security, Merkle Hash Tree, SIFT, image integrity

CLC Number:

TP309.2

ZHANG Xun, BAI Wanrong, WEI Feng, WANG Rong, TIAN Xiuxia, LIU Tianshun. An integrity auditing scheme based on MHT for power equipment images stored in the cloud[J]. Journal of East China Normal University(Natural Science), 2020, 2020(5): 33-43.

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