Author:
Izergin Dmitry,Eremeev Michael
Abstract
Development of the information space to an avalanche-like increase in the volume of mobile data on the Internet. The generated digital portraits of users are becoming one of the main products for sale. The high quality of user digital portraits and their number is achieved through the use of intelligent data processing methods and the presence of large data sets. The volume of data processed by mobile devices and the number of modern services that collect various types of information make the issue of ensuring the confidentiality of user information the most important. Existing security mechanisms for mobile operating systems, as a rule, are aimed at neutralizing harmful effects and do not ensure the safety of personal data from legitimate services. The article proposes a model for assessing the risks of compromising personal data on mobile devices based on the correlation analysis of public information about service developers in order to detect the possibility of aggregating data from various sources.
Reference24 articles.
1. Federal’nyj zakon ot 27.07.2006 N 152-FZ (red. ot 30.12.2020) «O personal’nyh dannyh» (s izm. i dop., vstup. v silu s 01.03.2021)
2. Detecting personally identifiable information transmission in android applications using light-weight static analysis
3. Yang J., Kim C., Hassan Onik M., 21st International Conference on Advanced Communication Technology, 425 (2019)
4. Personal Information Classification on Aggregated Android Application’s Permissions
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