Automated Privacy Code Analysis System for Data Flow Mapping
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current systems lack effective methods for assessing and ensuring compliance with privacy standards, particularly in software code, leading to vulnerabilities that can result in data breaches and non-compliance with privacy regulations.
Innovation Solution
A computer-implemented data processing system that calculates a risk level for privacy campaigns based on input campaign data, including personal data attributes, and generates a data flow diagram to identify potential vulnerabilities, while also monitoring changes in computer code to ensure compliance with privacy policies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional privacy audit practices are used, then privacy compliance assessment can be performed, but the process becomes bogged down due to lack of transparency into data flow and code vulnerabilities
Solution Approach 1:
The system performs preliminary analysis of code and data flow before the actual privacy audit takes place. By pre-identifying vulnerabilities, mapping data flows, and assessing risks in advance, the system prepares comprehensive information that speeds up the subsequent audit process and eliminates the need for time-consuming manual investigation during the audit itself.
Solution Approach 2:
The system introduces an intermediary automated analysis layer between the codebase and the privacy audit process. This intermediary automatically maps data flows, identifies vulnerabilities, and generates risk assessments, serving as a mediator that translates complex code structures into comprehensible privacy risk information for auditors.
2Measurement precision
If manual code analysis is performed to identify privacy vulnerabilities, then compliance can be assessed, but the process is time-consuming and resource-intensive
Solution Approach 1:
The system replaces manual mechanical code analysis with automated computational analysis. Using software agents and algorithms, the system automatically scans codebases, traces data flows, and identifies privacy vulnerabilities without human intervention, thereby maintaining detection accuracy while dramatically reducing the time and resources required.
Solution Approach 2:
The system changes the parameters of code analysis by using automated tools with configurable sensitivity levels, analysis depths, and detection criteria. This allows the system to adjust the thoroughness of analysis according to specific needs, achieving high precision vulnerability detection without always requiring maximum resource allocation.
3Loss of information
If comprehensive data flow mapping is implemented to improve transparency, then privacy risks can be better identified, but system complexity increases
Solution Approach 1:
The system segments the complex data flow mapping task into manageable components: individual data element tracking, path identification, transformation point detection, and risk assessment modules. By dividing the overall system into discrete functional segments, the complexity is distributed and each component can be developed and maintained independently while collectively providing comprehensive transparency.
Data Source
AI summary
In various embodiments, a data map generation system is configured to receive a request to generate a privacy-related data map for particular computer code, and, at least partially in response to the request, determine a location of the particular computer code, automatically obtain the particular computer code based on the determined location, and analyze the particular computer code to determine privacy-related attributes of the particular computer code, where the privacy-related attributes indicate types of personal information that the particular computer code collects or accesses. The system may be further configured to generate and display a data map of the privacy-related attributes to a user.