Institution profile

Shaanxi Key Laboratory for Network Computing and Security Technology

Academic institutionasia · cn
Research library1linked papers
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Selected work

Representative Papers

T-RBFT: A Scalable and Efficient Byzantine Consensus Based on Trusted Execution Environment for Consortium Blockchain

Apr 17, 2026

This work addresses the high communication overhead and limited performance of traditional Byzantine Fault Tolerance (BFT) consensus protocols in permissioned blockchains, even under the assumption that a majority of nodes are honest. To overcome these limitations, the paper proposes T-RBFT, a two-layer hybrid consensus mechanism leveraging Trusted Execution Environments (TEEs). T-RBFT dynamically partitions nodes into shards: within each shard, an optimized Raft protocol efficiently processes requests, while inter-shard consensus is achieved through a lightweight BFT protocol assisted by TEEs. This design substantially reduces communication complexity and latency, significantly enhancing throughput and scalability without compromising security. Experimental results demonstrate that T-RBFT outperforms existing two-layer consensus approaches in both efficiency and robustness.

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Recent publications

Latest Papers

T-RBFT: A Scalable and Efficient Byzantine Consensus Based on Trusted Execution Environment for Consortium Blockchain

Apr 17, 2026

This work addresses the high communication overhead and limited performance of traditional Byzantine Fault Tolerance (BFT) consensus protocols in permissioned blockchains, even under the assumption that a majority of nodes are honest. To overcome these limitations, the paper proposes T-RBFT, a two-layer hybrid consensus mechanism leveraging Trusted Execution Environments (TEEs). T-RBFT dynamically partitions nodes into shards: within each shard, an optimized Raft protocol efficiently processes requests, while inter-shard consensus is achieved through a lightweight BFT protocol assisted by TEEs. This design substantially reduces communication complexity and latency, significantly enhancing throughput and scalability without compromising security. Experimental results demonstrate that T-RBFT outperforms existing two-layer consensus approaches in both efficiency and robustness.

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