| The growing use of smartphones opens up new opportunities for development of software applications that support a broad spectrum of personal activities. These activities such as GPS usage, bank account management, instant messaging, and health monitoring often involve large volumes of private information. This leads to incentives to exploit mobile phones to attain person-specific information or invade privacy. A common way of getting access to valuable information stored on computers is through malware infection. Over the years, many malware detection techniques have been proposed. In this paper we examine behavioral analysis-based malware detection on smartphones. For this study, we developed six malware programs targeting the Android platform. We demonstrate that a malware program can be more resistant to behavioral analysis by randomizing its malicious activities, and thus better behavioral analysis based solutions are needed to detect malware with unpredictable behavioral patterns. |
