Scholarlink

<p>Wireless Sensor Networks (WSNs) are increasingly deployed in diverse commercial and industrial IoT applications, yet they remain vulnerable to security threats due to their wireless nature and resource constraints. While Information-Centric Networking (ICN) architectures improve data-centric security over conventional IP networks, internal attacks continue to challenge network reliability. To address these issues, we propose EPSTM, an Evolutionary Particle Swarm Optimized Trust Management Scheme, for authenticating IoT nodes and mitigating malicious behavior. The scheme evaluates trust using network-specific metrics, including device proximity, energy consumption, data transmission reliability, and message delivery timing, to guide secure routing decisions. Simulation results demonstrate that the proposed framework outperforms current state-of-the-art techniques, achieving reduced response times, minimized authentication delays, and lower request volumes from compromised nodes. Notably, for a network of 100 nodes, EPSTM achieved an accuracy of 98.66%, highlighting its efficacy in enabling secure, energy-efficient, and trustworthy IoT communication.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Energy-efficient trust management for secure IoT devices in information-centric wireless sensor networks

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年2月13日

查看全文
  • Jamal Alotaibi

摘要

Wireless Sensor Networks (WSNs) are increasingly deployed in diverse commercial and industrial IoT applications, yet they remain vulnerable to security threats due to their wireless nature and resource constraints. While Information-Centric Networking (ICN) architectures improve data-centric security over conventional IP networks, internal attacks continue to challenge network reliability. To address these issues, we propose EPSTM, an Evolutionary Particle Swarm Optimized Trust Management Scheme, for authenticating IoT nodes and mitigating malicious behavior. The scheme evaluates trust using network-specific metrics, including device proximity, energy consumption, data transmission reliability, and message delivery timing, to guide secure routing decisions. Simulation results demonstrate that the proposed framework outperforms current state-of-the-art techniques, achieving reduced response times, minimized authentication delays, and lower request volumes from compromised nodes. Notably, for a network of 100 nodes, EPSTM achieved an accuracy of 98.66%, highlighting its efficacy in enabling secure, energy-efficient, and trustworthy IoT communication.