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A scalable post quantum secure blockchain framework with adaptive time consensus in cloud environments.

M Velmurugan1, M Rajeev Kumar2

  • 1Department of Computer Science and Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai, 600062, Tamil Nadu, India. vtd1037@veltech.edu.in.

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Summary
This summary is machine-generated.

This study introduces PQ-PoETChain, a quantum-resistant blockchain model that significantly reduces energy consumption and improves performance. It enhances security against quantum attacks while maintaining high throughput for large-scale deployments.

Keywords:
BlockchainHash chain validationNTRU encryptionProof of elapsed timeQuantum cryptography

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Area of Science:

  • Computer Science
  • Cybersecurity
  • Distributed Systems

Background:

  • Blockchain technology faces scalability, energy, and quantum attack challenges.
  • Conventional systems (RSA, DSA, PoW, PoS) have high computational overhead.
  • Existing solutions are not optimized for cloud-scale execution.

Purpose of the Study:

  • To present PQ-PoETChain, a post-quantum-secure blockchain model.
  • To integrate NTRU signatures, adaptive Proof of Elapsed Time (PoET) in Trusted Execution Environments (TEEs), and Lightweight Hash Validation (LHV).
  • To evaluate the model's performance and security for cloud-native deployments.

Main Methods:

  • Implemented PQ-PoETChain in Python.
  • Evaluated the framework in a simulation environment with 50-1000 nodes.
  • Measured throughput, latency, and energy consumption through repeated trials.

Main Results:

  • NTRU signatures achieved sub-2 ms operations.
  • Adaptive PoET reduced consensus delay under load.
  • Achieved ~195 TPS with 189±4 ms latency at 500 nodes.
  • Reduced energy consumption by up to 91.8% compared to Proof of Work (PoW).
  • LHV lowered verification cost via constant-time hash-pointer validation.

Conclusions:

  • PQ-PoETChain offers a balanced combination of quantum-resilient security and improved performance.
  • The model is suitable for cloud-native and large-scale blockchain deployments.
  • Addresses key challenges in current blockchain technology.