Automated Source Code Scanning for Privacy Documentation
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Solution Overview
Problem
Organizations face challenges in documenting and managing the use of personal data within software applications, leading to increased risk of data privacy incidents and non-compliance with data privacy standards due to inadequate or absent code documentation by developers.
Innovation Solution
A system and method that analyzes computer code using rules-based or machine learning models to identify personal data usage, prompts users for input through a graphical interface, and populates documentation or questionnaires to ensure compliance with privacy impact assessments and data models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If developers write code without detailed documentation, then development speed and productivity are improved, but the ability to detect and measure privacy-related aspects of the code deteriorates
Solution Approach 1:
The patent replaces manual code documentation (mechanical process) with automated static analysis tools that use pattern recognition and machine learning algorithms to automatically detect privacy-related aspects in code, eliminating the need for developers to manually document while maintaining detectability
Solution Approach 2:
The system performs self-service by automatically analyzing code for privacy aspects without requiring developer intervention or manual documentation, where the analysis tool independently identifies PII handling patterns, data flows, and privacy risks in the codebase
2Reliability
If organizations implement comprehensive privacy policies and processes, then data privacy compliance is improved, but the complexity of managing and implementing these policies deteriorates
Solution Approach 1:
The patent replaces manual policy implementation and tracking with automated static analysis systems that continuously scan codebases for privacy-related patterns, automatically generating compliance reports and identifying policy violations without human intervention
Solution Approach 2:
The system implements continuous feedback loops where static analysis tools automatically detect privacy aspects, generate compliance status reports, and provide real-time feedback to organizations about their privacy posture, enabling continuous compliance monitoring without manual assessment
3Measurement precision
If developers provide detailed code documentation, then the accuracy of privacy impact assessment is improved, but the time required for code development increases
Solution Approach 1:
The patent applies preliminary action by performing static analysis of code for privacy aspects before the code is merged into the main repository or before compliance assessments are conducted, automatically identifying PII handling patterns and data flows in advance so that accuracy is achieved without delaying development
Solution Approach 2:
The system replaces manual documentation and assessment processes with automated pattern recognition algorithms that continuously scan code for privacy-related patterns, generating accurate privacy impact assessments automatically without requiring developer time investment
Data Source
AI summary
Data processing systems and methods according to various embodiments are adapted for automatically detecting and documenting privacy-related aspects of computer software. Particular embodiments are adapted for: (1) automatically scanning source code to determine whether the source code include instructions for collecting personal data; and (2) facilitating the documentation of the portions of the code that collect the personal data. For example, the system may automatically prompt a user for comments regarding the code. The comments may be used, for example, to populate: (A) a privacy impact assessment; (B) system documentation; and/or (C) a privacy-related data map. The system may comprise, for example, a privacy comment plugin for use in conjunction with a code repository.