Malware Detection Using Network Traffic Analysis in Android Based Mobile Devices

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.