Information Leakage Detection and Risk Assessment of Intelligent Mobile Devices

Abstract

(1) Background: Smart mobile devices provide conveniences to people’s life, work, and entertainment all the time. The basis of these conveniences is the data exchange across the entire cyberspace, and privacy data leakage has become the focus of attention. (2) Methods: First, we used the method of directed information flow to conduct an API test for all applications in the application market, then obtained the application data transmission. Second, by using tablet computers, smart phones, and bracelets as the research objects, and taking the scores of senior users on the selected indicators as the original data, we used the fusion information entropy and Markov chain algorithm skillfully to build a data leakage risk assessment mode to obtain the steady-state probability values of different risk categories of each device, and then obtained the entropy values of three devices. (3) Results: Tablet computers have the largest entropy in the risk of data leakage, followed by bracelets and mobile phones. (4) Conclusions: This paper compares the risk situation of each risk category of each device, and puts forward simple avoidance opinions, which might lay a theoretical foundation for subsequent research on privacy protection strategies, image steganography, and device security improvements.

Keywords

• directed information flow
• information disclosure
• information entropy
• Markov
• risk assessment