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TTEA: designing a quantum-ready and energy-conscious encryption model for secure IoT environments.

PubMed
Authors: Abdelaal MA, Moustafa AI, Saleh H, Afifi MYI

Year

2026

Paper ID

39195

Status

Peer-reviewed

Abstract Read

~2 min

Abstract Words

183

Citations

1

Abstract

The proliferation of resource-constrained IoT devices has intensified the conflict between robust security requirements and hardware limitations. Conventional lightweight encryption algorithms (e.g., TEA, Speck) often fail to resolve this tension, exhibiting known cryptanalytic vulnerabilities while imposing excessive computational and energy overhead. This paper presents the Two-Stage Encryption Approach (TTEA), an innovative cryptographic framework optimized for IoT ecosystems. TTEA incorporates a [Formula: see text] bit-sliced S-box as a non-linear substitution layer to ensure high diffusion and resistance to differential attacks, together with an adaptive key scheduling mechanism that dynamically adjusts computational complexity based on device power states. Evaluation on standard IoT platforms such as ESP32 and Raspberry Pi demonstrates that TTEA reduces energy consumption by 39% compared to TEA, lowers memory requirements by 40%, and achieves 20% faster execution speeds. Security analysis confirms an avalanche effect of 48.5% and near-ideal ciphertext entropy (7.98 bits for 128B packets). Furthermore, TTEA shows resilience against differential and linear cryptanalysis, side-channel attacks, and quantum threats when integrated with CRYSTALS-Kyber for post-quantum key exchange. By bridging the gap between post-quantum security and energy efficiency, TTEA offers a validated solution for modern IoT deployments.

Why This Paper Matters

  • This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
  • It adds a 2026 reference point for readers tracking recent quantum research.
  • The proliferation of resource-constrained IoT devices has intensified the conflict between robust security requirements and hardware limitations.

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External citation index: OpenAlex citation signal • updated 2026-10-28 04:44:27

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