摘要
设计了一种应用机器学习和D-S证据理论来进行Linux病毒检测的方案。主要包括方案的总体框架、样本特征选择方法、分类器选择、检测效果融合以及方案验证与结果分析等。在样本特征选择时引入了控制流程图的概念,在检测效果融合时使用了D-S证据理论的方法。最后在基于Weka软件的机器学习平台上实现和测试了该方案。验证结果表明,该Linux病毒检测方案具有良好的检测率和可靠性,可以应用于实际的商业产品中。
This paper mainly designs and realizes a Linux virus detection method using machine learning and D-S theory.It includes the design’s general framework,feature selection method,classifier selection method,detection result fusion and the design verification and result analysis.It intrdouces the control flow graph while doing feature selection,and introduces D-S theory while doing detection result fusion.Then it implements and test the method on the platform of Weka software.The results of implementation show that this design to detect Linux virus has high efficiency and good reliability,and it is adequate for commercial products.
出处
《单片机与嵌入式系统应用》
2014年第4期28-31,共4页
Microcontrollers & Embedded Systems
基金
国家重大专项"TD-SCDMA增强型多媒体手机终端的研发和产业化"(2009ZX03001-002-01)
