A Verifiable Transaction Selection Method for DAG Blockchain With VRF

Abstract

While directed acyclic graph (DAG) blockchain technologies improve scalability and throughput over traditional blockchains, they still face critical challenges, particularly in efficiently determining transaction order and ensuring verifiable transaction selection. These limitations significantly hinder their applicability in high-demand environments like IoT, where secure, high-throughput processing is essential. To address these issues, we propose a DAG-partitioned multichain architecture (DPMA), which generates distinct chains for each user node, enabling parallel transaction processing. In addition, we introduce a transaction selection algorithm with verifiable random function (TSAV), which implements a verifiable two-tier transaction selection process, ensuring secure and transparent transaction ordering. To further enhance security, we propose a dynamic transaction confidence analysis method that adjusts VRF parameters in response to network conditions. Experimental results demonstrate that our approach effectively identifies malicious behavior and improves transaction credibility. Compared to existing methods, our solution offers enhanced scalability and security, making it well-suited for large-scale decentralized applications.