Recognition method of privacy leakage behavior between Android components based on context information

Abstract

The invention discloses a recognition method of a privacy leakage behavior between Android components based on the context information. The method comprises the steps that firstly, communication parameter information between the components in an Android application program is extracted; secondly, according to the extracted communication parameter information between the components, two mutually communicated components in the Android application program are matched, and a component call chain is formed; thirdly, according to the component call chain information, static instrumentation is conducted on the Android application program, the two mutually communicated components are connected; fourthly, the application program codes obtained after instrumentation are subjected to static taint analysis, the behavior path associated with the privacy information transmission between the components is obtained, and the context information of the behavior path is extracted; fifthly, according to the obtained context information of the behavior path, whether the privacy information transmission behavior between the components is the privacy leakage behavior or not is judged. By means of the method and system, the accuracy of the communication analysis between the components is greatly improved.

Description

technical field [0001] The invention belongs to the technical field of mobile platform privacy leakage detection, and in particular relates to a method and system for identifying privacy leakage behaviors caused by communication between Android application program components. Background technique [0002] With the development of mobile terminal equipment, smart phones have become an indispensable part of people's daily life. Among the currently popular smart terminal operating systems, the Android system has the highest market share. Due to the low threshold of Android application development and the insufficient review of the application market, there are a large number of vulnerable applications and malicious applications in the third-party application market. A large amount of user privacy data is stored on mobile devices. Due to the existence of loopholes and malicious applications, user privacy data is leaked intentionally or unintentionally, which seriously threatens ...

AI Technical Summary

Problems solved by technology

However, this inter-component communication (ICC) mechanism can also be exploited by malicious applications, resulting in privacy leaks between components.

In order to slow down the privacy leakage behavior caused by communication between components, some researchers have performed ICC analysis on Android applications, but there are still deficiencies. For example, some existing studies have not linked source components and destination components to perform data flow analysis, Consider components not comprehensive, etc.

In addition, the data flow of sensitive information may be legitimate or malicious, and these proposed methods do not distinguish between legitimate privacy transmission behaviors and malicious privacy disclosure behaviors.

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