Blockchain-based privacy preservation in edge computing has emerged as a significant research area, focusing on leveraging blockchain’s decentralized, tamper-resistant, and transparent properties to secure sensitive data and enable trusted computation at the network edge. Research papers in this domain explore how blockchain can provide secure data sharing, access control, identity management, and auditability for edge devices while preserving user privacy. Studies highlight the integration of smart contracts, consensus mechanisms, and lightweight cryptographic techniques to ensure privacy without imposing excessive computational or energy overhead on resource-constrained edge nodes. Recent works also investigate hybrid frameworks combining blockchain with federated learning, AI-driven analytics, and multi-tier edge–fog–cloud architectures to achieve scalable, real-time, and privacy-aware services. Applications span smart healthcare, industrial IoT, autonomous vehicles, and smart cities, where sensitive information such as medical records, industrial data, and location-based data must be protected against unauthorized access and tampering. Additionally, challenges such as latency, scalability, and interoperability are addressed through optimized consensus algorithms, sharding, and off-chain solutions. Overall, blockchain-based privacy preservation in edge computing provides a robust, transparent, and decentralized framework to enable secure and privacy-aware next-generation edge applications.