Anti-Tampering Simulation Algorithm for Supply Chain Financial Big Data Based on Artificial Intelligence and Blockchain

Authors

  • Xiaoqing Wu College of Economics and Management, Chongqing Vocational and Technical University of Mechatronics, BiShan402760, Chongqing, China
  • Hongli Wu Guangdong Innovative Technical College, Dongguan 523000, Guangdong, China

Abstract

Social development and the progress of science and technology have driven the rapid advancement of computer technology. As an important research direction at this stage, computer vision multimodal learning of human-computer interaction has attracted the research interest of many scholars. Artificial intelligence (AI) and blockchain in terms of the multi-mode computer vision of human-computer interaction have also received a lot of attention. At present, AI has been widely used in various fields. Blockchain is mostly used for the prevention of data tampering and the protection of data security. Blockchain supply chain finance has encountered many problems in actual tamper proof applications. Many scholars have proposed corresponding countermeasures against the anti-tampering problem of blockchain. However, most of them focus on the identity of users and the privacy of transactions. There are few tamper proof studies on financial big data. On the basis of previous scholars’ research on blockchain, this paper proposes the anti-tampering algorithm of supply chain financial big data of artificial intelligence and blockchain and conducts empirical research. The research on AI and blockchain of computer vision multimodal learning of human-computer interaction showed that this method was feasible. When the number of pieces of information was 3050, the number tampered with after the application of the proposed method was 226 lower than that of traditional methods for counter attack. Regarding the security of data transmission, the number of pieces of information that had been tampered with was 101 lower than that secured by traditional methods. For the reliability of data storage, this method had 224 fewer tampered information than
traditional methods. This showed that the algorithm proposed in this paper was more resistant than traditional methods to attacks on the security of financial big data information of the supply chain, the protocol security during data transmission, and the reliability during data storage. At the same time, the research on AI and blockchain contributes to the development of computer vision multimodal learning for human-computer interaction.

Keywords: supply chain, financial big data, artificial intelligence and blockchain, tamper-proof simulation algorithm

Cite As

X. Wu, H. Wu, "Anti-Tampering Simulation Algorithm for Supply Chain Financial Big Data Based on Artificial Intelligence and Blockchain", vol. 34 no. 2, pp. 149-157, 2026.

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Published

2026-03-01

Issue

Vol. 34 No. 2 (2026): International Journal of Engineering Intelligent Systems

Section

Article

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