Mobile App Security Framework via Segmented Analysis

Resolve Bottlenecks,
Find Innovative Solutions
Generate Solutions

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

VSEngineering Contradiction Analysis

1Reliability

If comprehensive security analysis is performed on mobile applications, then security coverage is improved, but analysis time and computational resources increase

Engineering Contradiction:
Improvesecurity coverageVSAvoidanalysis time
Core Design Contradiction:
ReliabilityVSLoss of time

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.

Inventive Principle:
Principle #1Segmentation

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.

Inventive Principle:
Principle #10Preliminary action

2Reliability

If detailed security policy enforcement is implemented, then security reliability is improved, but system complexity increases

Engineering Contradiction:
Improvesecurity policy enforcementVSAvoidsystem complexity
Core Design Contradiction:
ReliabilityVSDevice complexity

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.

Inventive Principle:
Principle #24Intermediary (Mediator)

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.

Inventive Principle:
Principle #23Feedback

3Measurement precision

If comprehensive code analysis is performed, then detection precision is improved, but processing speed decreases

Engineering Contradiction:
Improvedetection precisionVSAvoidprocessing speed
Core Design Contradiction:
Measurement precisionVSProductivity

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.

Inventive Principle:
Principle #3Local quality

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.

Inventive Principle:
Principle #16Partial or excessive action

Data Source

PatentUS9009822B1Framework for multi-phase analysis of mobile applications
Publication Date: 2015.04.14 MAGENTA SECURITY HOLDINGS LLC
  • US9009822B1 patent drawing
  • US9009822B1 patent drawing
  • US9009822B1 patent drawing

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.