JCP, Free Full-Text

Por um escritor misterioso

Descrição

The evolution of mobile technology has increased correspondingly with the number of attacks on mobile devices. Malware attack on mobile devices is one of the top security challenges the mobile community faces daily. While malware classification and detection tools are being developed to fight malware infection, hackers keep deploying different infection strategies, including permissions usage. Among mobile platforms, Android is the most targeted by malware because of its open OS and popularity. Permissions is one of the major security techniques used by Android and other mobile platforms to control device resources and enhance access control. In this study, we used the t-Distribution stochastic neighbor embedding (t-SNE) and Self-Organizing Map techniques to produce a visualization method using exploratory factor plane analysis to visualize permissions correlation in Android applications. Two categories of datasets were used for this study: the benign and malicious datasets. Dataset was obtained from Contagio, VirusShare, VirusTotal, and Androzoo repositories. A total of 12,267 malicious and 10,837 benign applications with different categories were used. We demonstrate that our method can identify the correlation between permissions and classify Android applications based on their protection and threat level. Our results show that every permission has a threat level. This signifies those permissions with the same protection level have the same threat level.