Clustering: Keeping Malware Out in Android Applications

539 Words2 Pages

Due to the existence of malware samples in large amount of data malware detection techniques are introduced. Machine learning techniques are being applied to classify the applications focusing malware detection. Android has impressive growth in the domain of smart phones. Hence to overcome its better to group malware samples with structural similarities. Clustering technique in Android applications is an important technique in machine learning and gives automatic classi cation of applications by categorizing malware. Clustering keeps similar applications in one cluster and it gives good results with information retrieval. Following steps can be included in the process of applications clustering: 1. Android Manifest le speci es the permissions needed by the application. These les ask for permission to access restricted elements like hardware devices and contacts of the Android operating system. To cluster the malware behavior clustering algorithms such as hierarchical and partitioning-based clustering like K-Means or K-Medoids are used. Various clustering algorithms are discussed be...

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