Mobile App Security Framework via Segmented Analysis
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Solution Overview
Problem
The security of mobile application software on increasingly powerful mobile platforms is a concern due to the handling of sensitive information, as existing technologies lack efficient methods to determine the safety of applications and enforce security policies effectively.
Innovation Solution
A framework that includes a static instrumentation engine, dynamic runtime environment, central intelligence engine, platform-specific knowledge base, machine learning platform, and user-provided rules to analyze and test mobile applications, identifying 'regions of interest' and applying stimuli to determine their safety through a combination of behavior and logic engines and explorer engines.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If comprehensive security analysis is performed on mobile applications, then security coverage is improved, but analysis time and computational resources increase
Solution Approach 1:
The patent segments the security analysis process into multiple phases: static analysis phase, runtime analysis phase, and reporting phase. The analysis is divided into analyzing application code, identifying security policies, detecting violations, and generating reports. This segmentation allows the system to process different aspects of security analysis separately and efficiently, improving overall security coverage without proportionally increasing analysis time.
Solution Approach 2:
The patent performs preliminary static analysis of application code before runtime execution. Security policies are identified and security-critical regions are marked during the static analysis phase, so that during runtime analysis, the system can focus only on these pre-identified regions rather than analyzing entire application flows, significantly reducing runtime analysis time while maintaining comprehensive security coverage.
2Reliability
If detailed security policy enforcement is implemented, then security reliability is improved, but system complexity increases
Solution Approach 1:
The patent introduces an intermediary security analysis system that acts as a mediator between the mobile application and the operating system. This intermediary layer handles security policy enforcement by intercepting system calls and application behaviors, analyzing them against defined security policies, and enforcing restrictions when violations are detected. This approach maintains security reliability while managing system complexity through a dedicated security layer rather than embedding complex enforcement logic throughout the entire system.
Solution Approach 2:
The patent implements feedback mechanisms where the security analysis system continuously monitors application behavior, compares it against security policies, and provides real-time feedback by blocking or alerting on policy violations. The system learns from analysis results and adjusts its monitoring focus, providing feedback loops that improve security enforcement effectiveness while maintaining manageable system complexity through adaptive rather than purely deterministic control.
3Measurement precision
If comprehensive code analysis is performed, then detection precision is improved, but processing speed decreases
Solution Approach 1:
The patent applies local quality by focusing detailed analysis only on security-critical regions of the application code that are identified during static analysis. Instead of uniformly analyzing all code paths with the same depth, the system concentrates processing resources on regions marked as potentially security-relevant, achieving high detection precision for security issues while maintaining overall processing speed by reducing analysis intensity in non-critical areas.
Solution Approach 2:
The patent employs partial action by performing comprehensive static analysis on all application code to identify security policies and critical regions, then performing more intensive runtime analysis only on the subset of code that is actually executed and identified as security-critical. This partial approach to runtime analysis maintains high detection precision for security vulnerabilities while avoiding the excessive processing that would result from analyzing entire application flows at full depth during runtime.
Data Source
AI summary
A method is described that includes 1 receiving one or more user provided rules for an application of a mobile device through a user interface. The method also includes generating a representation of the application that describes various states and state transitions of the application. The method also includes referring to the one or more rules and the representation to identify a region of interest of the application. The method also includes configuring one or more monitors for the application to be enabled in a run time environment of the application. The method also includes setting conditions of the application within the run time environment to drive the application's execution to the region of interest. The method also includes observing behavior of the application and determining whether the region of interest corresponds to improperly behaving code.


