Abstract
The rapid growth of the Internet of Things (IoT) demands solutions that can secure massive streams of sensitive data without sacrificing performance. Traditional blockchains struggle in IoT environments, facing significant challenges with transaction speed, scalability, and privacy. This paper introduces PRIVOT, a novel blockchain architecture that integrates a Directed Acyclic Graph (DAG) for high-throughput consensus with lightweight zero-knowledge proofs (ZKPs) for confidential transactions, rateless coded computation for private analytics, and an AI-driven manager that dynamically balances security and efficiency. Our simulations show that PRIVOT significantly outperforms traditional blockchain approaches, achieving high transaction throughput (up to 480 TPS on a 500-device network) with confirmation latencies under 2.1 seconds, even under heavy load. The framework provides robust privacy, limiting data leakage to less than 0.1% against significant node collusion, while keeping computational overhead low enough for resource-constrained IoT devices. By unifying these techniques, PRIVOT offers a scalable and resilient solution ideal for large-scale IoT deployments where both high performance and strong privacy are paramount.
| Original language | English |
|---|---|
| Pages (from-to) | 137592-137602 |
| Number of pages | 11 |
| Journal | IEEE Access |
| Volume | 13 |
| DOIs | |
| State | Published - 2025 |
Keywords
- AI-driven privacy
- DAG-enabled consensus
- IoT security
- blockchain
- coded computation
- zero-knowledge proofs
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