Aljumah Abdullah
College of Computer Engineering and Sciences, Prince Sattam Bin Abdulaziz University, Al Kharj, Saudi Arabia.
Sci Rep. 2025 Mar 24;15(1):10066. doi: 10.1038/s41598-025-93690-2.
The rapid proliferation of mobile IoT devices with inadequate security measures has elevated security to a critical concern. Researchers have proposed various systems for vulnerability detection based on conventional frameworks. However, these approaches often face challenges such as high computational costs, limited storage capacity, and slow response times. To ensure robust protection against cyberattacks, modern security solutions must continuously monitor and analyze historical data across the entire IoT network. This paper introduces a distributed security framework for IoT networks, leveraging software-defined networking (SDN), blockchain, and edge computing to efficiently detect and mitigate IoT-based attacks. In the proposed framework, SDN facilitates network-wide data monitoring and analysis, enabling effective attack detection. Blockchain technology ensures decentralized and tamper-resistant attack identification, addressing potential vulnerabilities. Meanwhile, the edge computing paradigm enables real-time attack detection at the network edge, ensuring timely alerts. An experimental evaluation of the proposed framework demonstrates its superiority over traditional approaches in terms of detection accuracy (98.7%), false positive rate (1.2%) and response time (101.1 ms), highlighting its effectiveness in securing IoT networks.
安全措施不足的移动物联网设备迅速激增,使安全成为一个关键问题。研究人员基于传统框架提出了各种漏洞检测系统。然而,这些方法往往面临诸如高计算成本、有限的存储容量和缓慢的响应时间等挑战。为确保对网络攻击的强大防护,现代安全解决方案必须持续监控和分析整个物联网网络中的历史数据。本文介绍了一种用于物联网网络的分布式安全框架,利用软件定义网络(SDN)、区块链和边缘计算来有效检测和缓解基于物联网的攻击。在所提出的框架中,SDN有助于进行全网络的数据监控和分析,从而实现有效的攻击检测。区块链技术确保了分散式且抗篡改的攻击识别,解决了潜在的漏洞问题。同时,边缘计算范式能够在网络边缘进行实时攻击检测,确保及时发出警报。对所提出框架的实验评估表明,其在检测准确率(98.7%)、误报率(1.2%)和响应时间(101.1毫秒)方面优于传统方法,凸显了其在保障物联网网络安全方面的有效性。