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Hybrid Framework for Secure Low-Power Data Encryption with Adaptive Payload Compression in Resource-Constrained IoT

You-Rak Choi1, Hwa-Young Jeong2, Sangook Moon3

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Summary
This summary is machine-generated.

This study introduces a hybrid framework for resource-constrained IoT systems, balancing security and energy efficiency. It achieves significant data compression and enhanced cryptographic security, enabling 14-year autonomous operation for critical infrastructure monitoring.

Keywords:
IoT securityacoustic leak detectionadaptive compressionauthenticated encryptioncritical infrastructure monitoringenergy-efficient cryptographyhardware accelerationwireless sensor networks

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Area of Science:

  • Internet of Things (IoT) Security
  • Embedded Systems Energy Efficiency
  • Signal Processing for Sensor Networks

Background:

  • Resource-constrained IoT systems require both strong security and long operational life, especially for critical infrastructure monitoring.
  • A conflict exists between cryptographic security needs and energy efficiency in these devices.
  • Existing solutions often fail to adequately address both security and power consumption for long-term autonomous deployments.

Purpose of the Study:

  • To develop a hybrid framework that integrates signal-adaptive compression with hardware-accelerated encryption.
  • To resolve the trade-off between cryptographic security and energy efficiency in IoT systems.
  • To enhance the security and extend the operational lifetime of IoT devices for critical infrastructure monitoring.

Main Methods:

  • Implemented a Dynamic Payload Compression with Selective Encryption (DPCSE) framework.
  • Classified sensor data into three Signal-to-Noise Ratio (SNR) regimes for adaptive compression.
  • Integrated adaptive compression with hardware-accelerated Advanced Encryption Standard (AES) on an STM32L5 microcontroller.

Main Results:

  • Achieved an average payload reduction of 5.91-fold across 2714 acoustic sensor samples, with 100% detection accuracy.
  • Reduced power-data correlation from 0.820 to 0.041, significantly increasing resistance to differential power analysis attacks.
  • Extended projected operational lifetime to 14 years on standard batteries, exceeding industrial requirements.

Conclusions:

  • The DPCSE framework effectively balances security and energy efficiency in resource-constrained IoT systems.
  • Hardware-accelerated encryption combined with adaptive compression provides robust security against side-channel attacks.
  • The proposed system offers a viable solution for long-term, secure, and autonomous critical infrastructure monitoring.