An Overview of AI and Blockchain Integration for Privacy-Preserving
Zongwei Li, Dechao Kong, Yuanzheng Niu, Hongli Peng, Xiaoqi Li, Wenkai Li
TL;DR
The paper investigates privacy-preserving strategies at the intersection of artificial intelligence and blockchain, outlining core techniques such as zero-knowledge proofs, ring signatures, homomorphic encryption, secure multi-party computation, and differential privacy. It surveys integration scenarios including data encryption, de-identification, multi-layer ledgers, and k-anonymity, and evaluates systems across authority management, access control, data protection, network security, and scalability. By classifying AI–blockchain privacy applications into IoT, smart contracts/services, and large-scale data analytics, it identifies deficiencies and offers targeted recommendations to enhance reliability and privacy in real-world deployments. The work highlights future directions, notably leveraging edge computing and multi-chain architectures to improve efficiency and security in privacy-preserving AI–blockchain ecosystems.
Abstract
With the widespread attention and application of artificial intelligence (AI) and blockchain technologies, privacy protection techniques arising from their integration are of notable significance. In addition to protecting privacy of individuals, these techniques also guarantee security and dependability of data. This paper initially presents an overview of AI and blockchain, summarizing their combination along with derived privacy protection technologies. It then explores specific application scenarios in data encryption, de-identification, multi-tier distributed ledgers, and k-anonymity methods. Moreover, the paper evaluates five critical aspects of AI-blockchain-integration privacy protection systems, including authorization management, access control, data protection, network security, and scalability. Furthermore, it analyzes the deficiencies and their actual cause, offering corresponding suggestions. This research also classifies and summarizes privacy protection techniques based on AI-blockchain application scenarios and technical schemes. In conclusion, this paper outlines the future directions of privacy protection technologies emerging from AI and blockchain integration, including enhancing efficiency and security to achieve a more comprehensive privacy protection of privacy.