Information Leakage Detection and Risk Assessment of Intelligent Mobile Devices

(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 d...

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Bibliographic Details
Published in:Mathematics (Basel) 2022-06, Vol.10 (12), p.2011
Main Authors: Yang, Xiaolei, Liu, Yongshan, Xie, Jiabin
Format: Article
Language:English
Subjects:
Access control
Algorithms
Big Data
Cybercrime
Data exchange
Data transmission
directed information flow
Electronic devices
Entropy (Information theory)
Food science
information disclosure
information entropy
Information flow
Internet
Jewelry
Leak detection
Markov
Markov chains
Online instruction
Privacy
Risk assessment
Risk factors
Smartphones
Social networks
Software
Steganography
Tablet computers
Wireless networks
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Summary:(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.
ISSN:2227-7390
2227-7390
DOI:10.3390/math10122011