The Android operating system provides a rich Inter-Component Communication (ICC) method that brings enormous convenience. However, the Android ICC also increases security risks. To address this problem, a formal method is proposed to model and detect inter-component communication behavior in Android applications. Firstly, we generate data flow graphs and data facts for each component through component-level data flow analysis.Secondly, our approach treats ICC just like method calls. After analyzing the fields and data dependencies of the intent, we identify the ICC caller and callee, track the data flow between them, and construct the ICC model. Thirdly, the behavior model of Android applications is constructed by a formal mapping method for component data flow graph based on Pi calculus. The runtime sensitive path trigger detection algorithm is then given. Communicationbased attacks are detected by analyzing intent abnormity. Finally, we analyze the modeling and detection efficiency, and compare it with relevant methods. Analysis of 57 real-world applications partly verifies the effectiveness of the proposed method.

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Android is the most popular mobile platform, and it has become a primary malware target. Existing behavior-based Android malware detection methods suffer from false positive and false negative problems, which lead to low detection accuracy. Formal theory is crucial in studying the behaviors of Android applications characterized by high concurrency, interaction, and mobility. However, existing formal methods mainly focus on specific issues and lack the essential abstraction and high-level description of application behavior. In this study, we propose a formal method for the description and decision of application behavior based on process algebra. First, we propose a formal method for describing application behavior at a component level using process algebra. By extending π-calculus theory, we establish the mapping relationship from the Android application to process algebra, and present the semantics and evolution rules of behavior based on process algebra. Second, we describe the behavior of four types of components in applications and characterize concurrent interactions of components using process algebra expressions. Third, we define the behavior equivalence and simulation mechanism for application behavior analysis and propose the decision rules based on weak simulation. Finally, we discuss a demonstration case, which includes malicious behavior, to demonstrate the feasibility and effectiveness of the proposed method. The results show that our method can accurately describe and analyze application behavior, which provides theoretical support for technologies and methods of behavior-based detection.