SPBVPST : Towards Scalable and Private Blockchain Architectures by Integrating Verifiable Computation, Privacy-Preserving Sharding, and Trusted Execution Environments

The burgeoning importance of blockchain technology is hampered by significant challenges in scalability and privacy, limiting its broader application and efficacy in today's data-intensive landscapes. This paper addresses these critical issues by innovatively integrating Verifiable Computation, Privacy-Preserving Sharding based on Firefly Optimizer, and Trusted Execution Environments (TEEs). Existing approaches often compromise between scalability and privacy, leading to suboptimal performance metrics such as reduced throughput and increased communication delays. Furthermore, traditional methods lack robust, trust-based mechanisms for node selection, exacerbating these limitations. In contrast, our groundbreaking framework employs Spatial and Temporal Trust mechanisms for miner node selection and privacy preservation, respectively. The synergy of these components results in notable performance gains that include a 10.5% increase in throughput, a 4.5% reduction in energy consumption, a 9.4% decrease in communication delay, and a 2.9% increase in Packet Delivery Ratio (PDR) across various test scenarios. By offering a holistic, efficient, and secure approach, this paper sets a new benchmark for building scalable, verifiable, and privacy-preserving blockchain architectures, presenting a comprehensive solution to existing challenges.