K. A. Dhanya

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In this paper, we propose a statistical approach for smartphone malware detection. A set of features such as hardware, permission, application components, filtered intents, opcodes and strings are extracted from the samples to form a vector space model. Feature selection methods such as Entropy based Category Coverage Difference (ECCD) and Weighted Mutual(More)
The popularity and openness of Android platform encourage malware authors to penetrate various market places with malicious applications. As a result, malware detection has become a critical topic in security. Currently signature-based system is able to detect malware only if it is properly documented. This reveals the need to find new malware detection(More)
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