Abstract
The Android platform leads the mobile operating system marketplace and subsequently has drawn the interest of malware authors and researchers. The significant number of proposed malware detection techniques, classification models and practical reverse engineering solutions are insufficient and there is a lack of perfection. Also, the number of Android apps has increased significantly in recent years, as has the number of apps revealing confidential data. It is essential to investigate the applications and make sure that none of them are leaking privacy data, and consequently a privacy leak analysis approach is needed. Therefore, this paper investigates plus apps behavior and data leakages with a machine-learning algorithm to determine the best features for differentiating plus apps from original apps. The result of the analysis discloses that the SVM classifier presents the greatest accuracy. Further investigation demonstrates that the classifier with the ranking algorithm that uses correlation coefficient (CorEvel) and information gain (InfGain) methods offers more exceptional precision than the other correlation algorithms. The result of this experiment proves that the ranking algorithm is able to decrease the dimension of features and produce an accuracy of 96.60%.
Highlights
Operating systems (OSes) such as Android used in various applications today can be prone to certain risks
We present the results of risky permission ranking, application evolution, the extracted explicit privacy leakages features based on level of protection and PlusApps’ classification performance evaluation
The Android platform is an open ecosystem that allow its developers to tailor some of its default features and settings
Summary
Operating systems (OSes) such as Android used in various applications today can be prone to certain risks. When malicious code gets access to a user’s personal data and computer, controlling illegal computer systems and cyber source may be possible. In this case, the computer and network credibility, integrity and availability can be destroyed. An administrator could not treat every OS or application error as an attack, but certain characteristics that a security issue exists can be looked into. Some of these include crash outcomes after opening an e-mail attachment and after viewing a certain web page in a web browser. WhatsApp application versions will be investigated, both the plus and the original version from its existence
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