Optimized Cross-Chain Transactions With Aggregated Zero-Knowledge Proofs: Enhancing Efficiency and Security
Xiaoxuan Hu, Xiao Chen, Zhenjiang Dong, Yanfei Sun, Yufeng Guo, Bingyi Fang, Jin Qi · IEEE Internet of Things Journal · 2025
With the rapid development of the blockchain industry and the widespread adoption of IoT devices, which are often deployed on different blockchains, the need for cross-chain value and data exchange has become increasingly important. However, existing cross-chain transactions face challenges such as low efficiency, high costs, and insufficient security. To address these issues, this paper proposes a cross-chain transaction scheme based on aggregated zero-knowledge proofs. This scheme optimizes the allocation of computing resources in a distributed environment and employs a multi-branch balanced Merkle tree to construct aggregated zero-knowledge proofs, significantly reducing the verification costs for batch cross-chain transactions.To further enhance data privacy and integrity, this paper introduces the Secure Aggregated Block Verification (SABV) algorithm and improves system consistency and reliability through the Local Merkle Tree Rebalance (LMTR) algorithm. In addition, this paper analyzes the basic security of the proposed scheme when implemented in adversarial environments and provides countermeasures for common threats in distributed systems. Finally, simulations and actual deployment on the Ethereum test network were conducted. The results indicate that our method reduces CPU usage, memory consumption, and time expenditure by 50.10%, 99.03%, and 99.47%, respectively, during the generation of zero-knowledge proofs for batch cross-chain transactions. At the same time, building upon the performance improvements of the existing zero-knowledge proofs, our approach also demonstrates significant enhancements in contract deployment and cross-chain transaction efficiency.