Hartley的测试对Android恶意软件分析的操作码进行了排序

Meenu Mary John, P. Vinod, K. Dhanya
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引用次数: 3

摘要

Android平台的普及和开放性促使恶意软件作者利用恶意软件渗透到各种市场。因此,恶意软件检测已成为安全领域的一个重要课题。目前基于签名的系统能够检测到恶意软件,如果它是正确的记录。这表明需要寻找新的恶意软件检测技术。在我们的框架中,提出了一种利用从各种应用程序中提取的操作码进行Android恶意软件检测的统计技术。该技术针对来自传染病数据集的恶意apk样本和来自不同市场的良性apk样本进行了评估。使用哈特利测试确定导致误分类率降低的突出特征。
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Hartley's test ranked opcodes for Android malware analysis
The popularity and openness of Android platform encourage malware authors to penetrate various market places with malicious applications. As a result, malware detection has become a critical topic in security. Currently signature-based system is able to detect malware only if it is properly documented. This reveals the need to find new malware detection techniques. In our framework, a statistical technique for Android malware detection using opcodes extracted from various applications is proposed. This technique is evaluated against malware apk samples from contagio dataset and benign apk samples from various markets. The prominent features that result in reduced misclassification rates are determined using Hartley's test.
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