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SWEAT: symmetric wearable encryption algorithm for the internet of medical things

  • Muhammad Zulfiqar Khan
  • , Muhammad Maaz Rehan
  • , Muhammad Nadeem
  • , Ehsan Ullah Munir
  • , Saima Gulzar Ahmad
  • , Muhammad Waqas Rehan
  • , Naeem Ramzan

    Research output: Contribution to journalArticlepeer-review

    Abstract

    The rapid expansion of IoT, particularly wearable health monitoring devices, demands robust security to protect sensitive data against vulnerabilities and unauthorized access. However, ensuring security in resource-constrained medical IoT devices remains challenging due to limited processing power, memory, battery life, and security level. To address this, this work proposes Symmetric Wearable Encryption Algorithm for the Internet of Medical Things (SWEAT), a lightweight cryptographic scheme designed for secure data transfer in low-power wearable IoT devices. SWEAT introduces an efficient and optimized encryption mechanism with simplified key generation, random padding, and reduced encryption rounds, operating on a 128-bit block with a single-round design. The algorithm integrates seamlessly with fog nodes while ensuring data confidentiality and resistance against intruders. Experimental evaluation shows that SWEAT achieves competitive performance compared with the state-of-the-art Dynamic Light Weight Symmetric Encryption Algorithm (DLSEA) and Dynamic Lightweight Symmetric (DLS) algorithm, while significantly reducing computational cost and power consumption. These results highlight SWEAT as a secure, energy-efficient, and real-time solution for wearable healthcare monitoring applications.
    Original languageEnglish
    Article number101892
    Number of pages22
    JournalInternet of Things
    Volume37
    Early online date23 Feb 2026
    DOIs
    Publication statusPublished - 9 Mar 2026

    Keywords

    • symmetric cryptography
    • wearable IoT
    • internet of medical things (IoMT)
    • lightweight encryption
    • block cipher
    • particle swarm optimization
    • remote health monitoring

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