@benjaminent
This study optimizes zero-knowledge proof (ZKP) schemes for blockchain transaction privacy by enhancing proof generation efficiency and reducing verification overhead. Techniques like zk-SNARKs are refined through recursive proof composition and batch verification, minimizing on-chain data exposure. Adaptive parameter selection balances security and computational costs, while hardware acceleration (e.g., GPUs/FPGAs) speeds up cryptographic operations. The optimized scheme ensures anonymity without compromising scalability, addressing privacy needs in permissionless blockchains.
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