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Perception is a fundamental psychological process that enables individuals to organize, interpret, and consciously experience sensory information. This process is crucial for understanding and interacting with the world around us. It includes both bottom-up and top-down processing, each playing a distinct role in how we perceive our environment.
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SNPL: One Scheme of Securing Nodes in IoT Perception Layer.

Yongkai Fan1,2,3, Guanqun Zhao3, Kuan-Ching Li4

  • 1Institute of Computer Science and Cybersecurity, Communication University of China, Beijing 100024, China.

Sensors (Basel, Switzerland)
|February 22, 2020
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Summary

This study introduces Securing Nodes in IoT Perception Layer (SNPL), a novel security scheme using lightweight algorithms to protect Internet of Things (IoT) devices. SNPL effectively defends against data tampering and unauthorized access, ensuring trustworthy data analysis.

Keywords:
IoTIoT nodessecuritysecurity framework

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Area of Science:

  • Computer Science
  • Cybersecurity
  • Network Security

Background:

  • Data trustworthiness is critical for big data analysis, especially in cyber-physical systems where sensors collect most data.
  • The proliferation of Internet of Things (IoT) nodes increases security vulnerabilities, risking data tampering, unauthorized access, and identity fraud, leading to significant economic and social losses.

Purpose of the Study:

  • To propose a novel security scheme, Securing Nodes in IoT Perception Layer (SNPL), designed to protect nodes within the IoT perception layer.
  • To ensure the security and performance requirements of IoT networks while mitigating risks associated with vulnerable nodes.

Main Methods:

  • Development of SNPL, incorporating novel lightweight algorithms for enhanced security.
  • Integration of safety technologies to provide security isolation for sensitive operations within IoT nodes.
  • Conducting experiments with diverse node types and quantities to evaluate the scheme's effectiveness.

Main Results:

  • Experimental results demonstrate that SNPL is efficient and effective in safeguarding IoT networks against faulty or malicious nodes.
  • Performance analysis confirms the scheme's capability to maintain security without compromising network performance.

Conclusions:

  • SNPL provides a robust solution for securing the IoT perception layer, crucial for maintaining data integrity and system reliability.
  • The proposed scheme shows potential for practical implementation in real-world IoT applications, enhancing overall system security and trustworthiness.