MadeCR:基于关联的认知无线电恶意软件检测

Yanzhi Dou, K. Zeng, Yaling Yang, D. Yao
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引用次数: 12

摘要

认知无线电(CR)是一种提高频谱利用率的智能无线电技术,在不久的将来有可能得到广泛应用。然而,其灵活的面向软件的设计可能被对手利用来控制CR设备,从而对各种关键无线基础设施发动大规模攻击。为了主动缓解潜在的严重威胁,本文提出了基于关联的CR恶意软件检测系统MadeCR, MadeCR利用CR应用程序组件操作之间的相关性来检测恶意行为。此外,本文的一个重要贡献是一种称为突变测试的通用实验方法,以全面评估异常检测方法对大量人为恶意软件案例的有效性。评估表明,MadeCR在1.10s内检测到恶意行为,准确率为94.9%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
MadeCR: Correlation-based malware detection for cognitive radio
Cognitive Radio (CR) is an intelligent radio technology to boost spectrum utilization and is likely to be widely spread in the near future. However, its flexible software-oriented design may be exploited by an adversary to control CR devices to launch large scale attacks on a wide range of critical wireless infrastructures. To proactively mitigate the potentially serious threat, this paper presents MadeCR, a Correlation-based Malware detection system for CR. MadeCR exploits correlations among CR applications' component actions to detect malicious behaviors. In addition, a significant contribution of the paper is a general experimentation method referred to as mutation testing to comprehensively evaluate the effectiveness of the anomaly detection method against a large number of artificial malware cases. Evaluation shows that MadeCR detects malicious behaviors within 1.10s at an accuracy of 94.9%.
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