Development of an Accounting Informatization Model Through Cloud Data Integrity Verification

This manuscript explores the application of cloud data integrity verification algorithms to improve accounting informatization in enterprises. The proposed method enhances financial management by streamlining the verification of cloud-based financial data, addressing challenges related to data accuracy and security. A multi-user parallel verification algorithm is introduced, reducing verification load and improving the detection of damaged data blocks compared to traditional methods. After 100 rounds of testing, the proposed method outperformed data mining (DM) and artificial intelligence (AI) algorithms, identifying 127 damaged data blocks, versus 110 and 118, respectively. The findings show that increased verification rounds lead to better identification of damaged data, demonstrating the algorithm's superior performance.