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<p>6G technology represents a revolutionary step in the development of smart cities, with the increased usage of the Internet of Things (IoT) in various industries. However, as IoT devices are increasingly integrated into the vital functions of society, there is a need to address the dangers of security vulnerabilities in the networks. This study proposes a novel encryption system to ensure the security of encrypted data. The proposed model is based on the dynamic Galois field expansion algorithm (DGFEA) and the chimp and spotted hyena optimization techniques. Data pre-processing was carried out using K-nearest neighbors (KNNs) and min–max normalization, while the Reed-Solomon codes have been used for error correction. The model is evaluated using peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), time for encryption, time for decryption, and time for key generation, with the model’s performance being compared against other four other data transmission frameworks: quantum-inspired quantum walks (QIQW), quantum-based secure and lightweight transmission (QSLT), location-aware cryptosystem (LACS), and quantum-designated verifier signature (QDVS). The model demonstrates high robustness and speed, scoring PSNR of 35, SSIM of 0.98, time for encryption of 4.21&#xa0;s, time for decryption of 3.36&#xa0;s, and time for key generation of 2.18&#xa0;s. The proposed model demonstrates higher performance over the benchmark models, demonstrating the superiority of the proposed model in quantum-resistant encryption scenarios.</p>

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Secure IoT transmission in 6G smart cities: a quantum-resilient hybrid Galois field and Reed-Solomon approach

  • 期刊论文

  • 发表日期：

    2025年3月5日

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  • Raneem Y. Alyami

摘要

6G technology represents a revolutionary step in the development of smart cities, with the increased usage of the Internet of Things (IoT) in various industries. However, as IoT devices are increasingly integrated into the vital functions of society, there is a need to address the dangers of security vulnerabilities in the networks. This study proposes a novel encryption system to ensure the security of encrypted data. The proposed model is based on the dynamic Galois field expansion algorithm (DGFEA) and the chimp and spotted hyena optimization techniques. Data pre-processing was carried out using K-nearest neighbors (KNNs) and min–max normalization, while the Reed-Solomon codes have been used for error correction. The model is evaluated using peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), time for encryption, time for decryption, and time for key generation, with the model’s performance being compared against other four other data transmission frameworks: quantum-inspired quantum walks (QIQW), quantum-based secure and lightweight transmission (QSLT), location-aware cryptosystem (LACS), and quantum-designated verifier signature (QDVS). The model demonstrates high robustness and speed, scoring PSNR of 35, SSIM of 0.98, time for encryption of 4.21 s, time for decryption of 3.36 s, and time for key generation of 2.18 s. The proposed model demonstrates higher performance over the benchmark models, demonstrating the superiority of the proposed model in quantum-resistant encryption scenarios.