Abstract: A consensus mechanism based on node reputation values is proposed to address malicious attacks on nodes in the IOTA network. In RV_IOTA, a dynamic reputation value system with time decay is introduced. The reputation value of nodes is adjusted based on their historical transaction performance: valid transactions lead to an increase in the reputation value, while conflicting transactions (such as double-spending attacks) cause a decrease in it, thereby limiting the influence of malicious nodes. RV_IOTA optimizes the selection of Tips algorithm based on node reputation values, which adjusts the probability of Tips being referenced according to reputation values and cumulative transaction weights, making transactions issued by high-reputation nodes more likely to be verified. The proposed mechanism effectively suppresses double-spending attacks in the early stage of the network, reduces the success rate of attacks, and restricts the transaction submission capabilities of malicious nodes, promoting honest nodes to dominate the consensus process and ensuring the robustness and security of the network. Experimental results show that with a scale of 500 nodes, RV_IOTA achieves a throughput of 39 TPS, a 15% improvement over traditional IOTA. Meanwhile the transaction confirmation delay for high-reputation nodes is reduced to 1.2 seconds. By reducing the verification scope of Tips selection from global to neighborhood, the algorithm complexity is decreased. With only a 25% increase in memory overhead, it provides an efficient and reliable decentralized solution for IoT applications.

Key words: reputation value, time decay function, optimal selection of Tips, dynamic consensus mechanism, malicious node detection