Despite enabling automated systems and data connectivity, the Internet of Things (IoT) presents security problems, especially about data confidentiality and integrity during transmission. When applied to the problem, traditional cryptographic techniqueslike the Diffie-Hellman (D-H) key exchange algorithm are susceptible to man-in-the-middle (MitM) attacks, which calls for more effective solutions. To reduce computational overhead and improve security in Internet of Things (IoT)-based wireless sensor networks (WSNs), this study suggests the Residue Number Key Exchange (RNKE) technique. In this new RNKE, the Residue Number System (RNS) is used. RNKE was evaluated using Python simulations. According to the simulation, RNKE outperformed the DH-SHA-512, DNA-DH, BaaS-HF, and MLSRP by 99.91% in terms of energy usage. Additionally, it outperformed the current ones in terms of speedier runtime, outperforming them by 99.56%. In comparison to current techniques, RNKE also decreased average PLR (APLR) by 19–56.99%. The suggested RNKE is appropriate for real-time protected data applications in dynamic contexts as it protects data and guarantees fast transmission.

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Improving Data Security in IoT Communication with the Residue Number Key Exchange Method

  • Prince Modey,
  • Gaddafi Abdul-Salaam,
  • William Leslie Brown-Acquaye,
  • Emmanuel Freeman,
  • Israel Edem Agbehadji,
  • Richard C. Millham

摘要

Despite enabling automated systems and data connectivity, the Internet of Things (IoT) presents security problems, especially about data confidentiality and integrity during transmission. When applied to the problem, traditional cryptographic techniqueslike the Diffie-Hellman (D-H) key exchange algorithm are susceptible to man-in-the-middle (MitM) attacks, which calls for more effective solutions. To reduce computational overhead and improve security in Internet of Things (IoT)-based wireless sensor networks (WSNs), this study suggests the Residue Number Key Exchange (RNKE) technique. In this new RNKE, the Residue Number System (RNS) is used. RNKE was evaluated using Python simulations. According to the simulation, RNKE outperformed the DH-SHA-512, DNA-DH, BaaS-HF, and MLSRP by 99.91% in terms of energy usage. Additionally, it outperformed the current ones in terms of speedier runtime, outperforming them by 99.56%. In comparison to current techniques, RNKE also decreased average PLR (APLR) by 19–56.99%. The suggested RNKE is appropriate for real-time protected data applications in dynamic contexts as it protects data and guarantees fast transmission.