A Malware Signature Extraction and Detection Method Applied to Mobile Networks

Guoning Hu, D. Venugopal
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引用次数: 23

Abstract

The rapid development of mobile phone networks has facilitated the need for better protection against malware. Malware detection is a core component of a security system protecting mobile networks. In this paper, we describe a system for detecting malware within the network traffic using malware signatures. Our system contains two key components. The first one automatically extracts a set of signatures from existing malware samples. In particular, we reduce the number of signatures by using a common signature for a malware and its variants. In addition, we minimize the total false alarm rate of malware detection by extracting signatures that are most uncommon within mobile network traffic. The second one is an efficient method that scans the network traffic using a hash table and sub-signature matching. Our evaluation on Symbian viruses show that our system detects existing malware and their new variants within the network traffic efficiently.
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一种应用于移动网络的恶意软件签名提取与检测方法
移动电话网络的快速发展促进了对恶意软件更好保护的需求。恶意软件检测是移动网络安全系统的核心组成部分。在本文中,我们描述了一个使用恶意软件签名检测网络流量中的恶意软件的系统。我们的系统包含两个关键组件。第一个自动从现有的恶意软件样本中提取一组签名。特别是,我们通过对恶意软件及其变体使用通用签名来减少签名的数量。此外,我们通过提取移动网络流量中最不常见的签名,将恶意软件检测的总误报率降至最低。第二种方法是使用哈希表和子签名匹配扫描网络流量的有效方法。我们对塞班病毒的评估表明,我们的系统可以有效地检测到网络流量中的现有恶意软件及其新变种。
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