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After the comprehensive survey of existing malware analysis products in the market, the survey result has shown that an assistive tool is needed to help researchers to automatically predict an Android malware in a given large number of applications. Due to a large volume of Android applications being developed and distributed every day through third party application stores, it is difficult to detect...
Predicting application performing malicious activity based on its behavioural analysis is extremely difficult compare to signature based approach. But considering the rapid development and slight changes in code allowing avoiding of signature-based malware analysis has made behaviour-based analysis more and more important in recent years. In last decade there is unimagined and trilling growth in the...
The authors have developing mobile device evaluation and testing platform to evaluate the mobile malware. Using the platform, the authors have created several courses in mobile device security. One of the important requirements is to provide students with a safe and sandboxed environment for malware analysis. Other features include tool enhanced lab environment, updated malware repository, log collection...
Increased use of Android devices and its open source development framework has attracted many digital crime groups to use Android devices as one of the key attack surfaces. Due to the extensive connectivity and multiple sources of network connections, Android devices are most suitable to botnet based malware attacks. The research focuses on developing a cloud-based Android botnet malware detection...
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