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Malware Detection Using Network Traffic Analysis in Android Based Mobile Devices

机译:在基于Android的移动设备中使用网络流量分析进行恶意软件检测

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Smart phones, particularly Android based, have attracted the users community for their feature rich apps to use with various applications like chatting, browsing, mailing, image editing and video processing. However the popularity of these devices attracted the malicious attackers as well. Statistics have shown that Android based smart phones are more vulnerable to malwares compared to other smart phones. None of the existing malware detection techniques have focused on the network traffic features for detection of malicious activity. To the best of our knowledge, almost no work is reported for the detection of Android malware using its network traffic analysis. This paper analyzes the network traffic features and builds a rule-based classifier for detection of Android malwares. Our experimental results suggest that the approach is remarkably accurate and it detects more than 90% of the traffic samples.
机译:智能手机(尤其是基于Android的智能手机)以其功能丰富的应用程序吸引用户社区,这些应用程序可与诸如聊天,浏览,邮件,图像编辑和视频处理之类的各种应用程序一起使用。但是,这些设备的普及也吸引了恶意攻击者。统计数据表明,与其他智能手机相比,基于Android的智能手机更容易受到恶意软件的攻击。现有的恶意软件检测技术都没有关注用于检测恶意活动的网络流量功能。据我们所知,几乎没有报道使用其网络流量分析来检测Android恶意软件的工作。本文分析了网络流量功能,并建立了基于规则的分类器来检测Android恶意软件。我们的实验结果表明,该方法非常准确,可以检测到90%以上的流量样本。

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