Automatic Feature Extraction, Categorization and Detection of Malicious Code in Android Applications
This addresses the need for automatic malware detection for Android users and developers, but it appears incremental as it builds on existing static analysis methods.
The paper tackles the problem of detecting malware in Android applications by proposing a static analysis approach that extracts features based on intents and permissions, categorizes apps, and identifies misuse of features, though no concrete detection results or numbers are provided.
Since Android has become a popular software platform for mobile devices recently; they offer almost the same functionality as personal computers. Malwares have also become a big concern. As the number of new Android applications tends to be rapidly increased in the near future, there is a need for automatic malware detection quickly and efficiently. In this paper, we define a simple static analysis approach to first extract the features of the android application based on intents and categories the application into a known major category and later on mapping it with the permissions requested by the application and also comparing it with the most obvious intents of category. As a result, getting to know which apps are using features which they are not supposed to use or they do not need.