Detection of Android Applications Homology Based on the Authors’ Programming Style

As the mobile internet playing an increasingly important role in people’s daily life, the copyright issue of Android applications attaches more and more attentions. Because Android applications are vulnerable to reverse engineering, there are many criminals illegally modify and re-sign the official android for their own interests, which has seriously damaged the user’s rights and disturbed the order of the mobile internet. In this paper, a novel detects method of Android applications similarity based on the authors’ programming style is described. In the proposed method, we firstly extract a series of basic features that can represent the programming style of author. Considering that the features selected manually are highly subjective, we tried ICA, PCA and LDA to optimize the features. Ultimately, an Extreme Learning Machine (ELM) model is trained with sequences of feature vectors. The results of experiments demonstrate that our proposed method has better performance than string comparison and grammar tree analysis when fighting against variable substitution, insert independent statement and data stream confusion.