A method for alerting mobile app privacy leaks

Abstract

The invention discloses an alarm method for mobile app privacy leakage, which is divided into two stages: offline and online. In the offline stage, the server side first evaluates the rationality of each category of app's request for each permission, and then clusters the user's privacy preferences, and establishes a corresponding privacy profile. In the online phase, the client first determines the user's privacy preference and downloads the corresponding privacy configuration file; then periodically calculates the authorization decision corresponding to the maximum profit of running the app in the memory, and notifies the mobile phone user to update the authorization policy accordingly through the alarm mechanism. The mobile phone privacy security mechanism of the present invention is simple and easy to implement, not only can meet the user's personalized privacy requirements, but also can take into account the privacy protection of data access and the usability of apps.

Description

technical field [0001] The invention relates to the field of privacy protection of intelligent mobile terminals, in particular to an alarm method for mobile app privacy leakage. Background technique [0002] In the mobile Internet, most users use smartphones for communication, which have independent operating systems, such as IOS, Android, Microsoft, etc. Users can freely install games, software, and applications developed by third-party providers on their phones for expansion. At the same time, with the rapid development of the Internet industry, the functions of smartphones are characterized by personalization, diversification, and intelligence, and will become a new area of ​​privacy leakage. It is precisely because of the above-mentioned characteristics of smart phones that some APP providers obtain private information such as user locations, text messages, address books, and picture files to provide services, which significantly increases the privacy and security risks ...

AI Technical Summary

Problems solved by technology

However, the existing privacy warning methods still have the following defects: ① The measurement model of privacy risk and app usability has not been established, and the balance between data access privacy protection and app usability cannot be considered; ② Lack of consideration of user privacy preferences, privacy warning information cannot meet user personality ③Users must independently evaluate the security of app permissions based on privacy warning information, increasing the burden on users

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