Title: A data integrity detection method for accounting informatisation based on homomorphic hash function

Authors: Guang Zhao; Zhi Li

Addresses: Business School, Xi'an Siyuan University, Xi'an 710038, China ' Department of Arts and Sciences, Xi'an Siyuan University, Xi'an 710038, China

Abstract: In order to solve the problems of low data detection accuracy and high detection time overhead, this paper proposes an accounting information data integrity detection method based on homomorphic hash function. First, the accounting data is collected by data mining method and the strong relevance of the data is determined by association rules. Then, set the distance matrix to determine the data key points, match the niche factor between the data key points, and complete the feature extraction. Finally, the binary code is used to mark the accounting information data, and the anti-collision of homomorphic hash function is used to complete the projection of accounting data, so as to realise the data integrity detection. The results show that the detection accuracy of this method is up to 98%, and the detection time overhead is within 4S, which shows that this method can effectively improve the integrity detection effect.

Keywords: homomorphic hash function; accounting informatisation; data detection; integrity: association rules.

DOI: 10.1504/IJITM.2025.144108

International Journal of Information Technology and Management, 2025 Vol.24 No.1/2, pp.13 - 26

Received: 26 May 2022
Accepted: 23 Sep 2022
Published online: 28 Jan 2025 *

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