MadeCR: Correlation-based malware detection for cognitive radio

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

Abstract

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%.
MadeCR:基于关联的认知无线电恶意软件检测
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。
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