An APP Privacy Information Leakage Detection Method Based on Deep Learning

With the increasing number and types of APP vulnerabilities, the detection technology and methods need to be enriched and personalized according to different types of security vulnerabilities. Therefore, a single detection technology can no longer meet the needs of business security diversity. First of all, the new detection method needs to clarify the relevant features of APP business security; Secondly, the new detection method needs to re-adapt the features related to APP business security; Thirdly, the new detection method needs to be trained and applied according to different AI algorithms. In view of this, we designed an APP privacy information leakage detection scheme based on deep learning. This scheme specifically selects business security-related features for the type of privacy information leakage vulnerability of APP, and then performs feature processing and adaptation to become the input parameters of CNN network algorithm. Finally, we train and call the CNN network algorithm. We selected the APP of the Telecom Tianyi Space App Store for experiment to evaluate the effectiveness of our APP privacy information leakage detection system based on CNN network. The experimental results show that the detection accuracy of our proposed detection system has achieved the desired effect.