基于频谱感知的油气物联网安全分析  

Security analysis of oil and gas IoT based on spectrum sensing

作　　者：卢永辉 詹杰[2] LU Yong-hui;ZHAN Jie(Shaxi Vocational School of Zhongshan,Zhongshan 528471,Guangdong Province,China;College of Physical and Electronic Sciences,Hunan University of Science and Technology,Xiangtan 411100,Hunan Province,China)

机构地区：[1]中山市沙溪理工学校,广东中山528471 [2]湖南科技大学物理与电子科学学院,湖南湘潭411100

出　　处：《信息技术》2025年第3期86-92,共7页Information Technology

基　　金：教育部高等学校科学研究发展中心(ZJXF2022302)。

摘　　要：为了解决油气物联网设备接入风险问题。对于独立攻击场景,提出一种基于隐马尔可夫的频谱感知数据检测模型,通过检测与概率统计实现风险数据检测。对于共谋攻击,采用频繁项集获得主要信息,并在融合中心处理数据实现风险检测。在独立攻击误差率检测中,恶意设备占比为50%,所提方法误差率为0.443,远低于其他技术。在共谋攻击检测率测试中,所提方法恶意设备数量占比在97%范围内时检测有效,优于另外两种方法。由此可见,所提方法在攻击检测中具有出色的安全检测效果,为油气物联网的稳定应用与安全提供了重要技术支持。To address the risk of connecting oil and gas IoT devices.For independent attack scenarios,a spectral sensing data detection model based on hidden Markov is proposed,which achieves risk data detection through detection and probability statistics.For collusion attacks,frequent item sets are used to obtain the main information,and data is processed in the fusion center to achieve risk detection.In independent attack error rate detection,malicious devices account for 50%,and the proposed method has an error rate of 0.443,which is much lower than other techniques.In the collusion attack detection rate test,the proposed method is effective when the proportion of malicious devices is within the range of 97%,which is superior to the other two methods.From this,it can be seen that the proposed method has excellent security detection performance in attack detection,providing important technical support for the stable application and security of the oil and gas Internet of Things.

关 键 词：频谱感知 油气物联网 安全 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]