Detecting software vulnerabilities in android using static analysis

Abstract

Now a day's mobile devices like Smartphone, tablets and Personal Digital Assistants etc. were playing most essential part in our daily lives. A high-end mobile device performs the same functionality as computers. Android based smart phone has become more vulnerable, because of an open source operating system. Anyone can develop a new application and post it into android market. These types of applications were not verified by authorized company. So it may include malevolent applications it may be virus, spyware, worms, etc. which can cause system failure, wasting memory resources, corrupting data, stealing personal information and also increases the maintenance cost. Due to these reasons, the mobile phone security or mobile security is very essential one in mobile computing. In the existing system is not able to detect new viruses, due to the limitation of updated signatures. The proposed system aims to motivate static code analysis based malware detection using search based machine learning algorithm which is called N-gram analysis and it detects the unnoticed malicious characteristics or vulnerabilities in the mobile applications.