Source Code Privacy Annotations for Faster Sensitive Data Detection
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Solution Overview
Problem
Existing software applications face challenges in detecting and protecting sensitive data such as Personally Identifiable Information (PII) and Protected Health Information (PHI) from unauthorized disclosure, as compilers fail to catch coding errors that breach privacy, and large codebases make it difficult to identify privacy breaches, logic errors, and security vulnerabilities.
Innovation Solution
Implementing a privacy-relevant data analyzer that scans source code to detect privacy-relevant data, generates reports of issues, and provides annotations to ensure compliance with privacy guidelines, using machine-based reasoning for efficient scanning with minimal runtime cost.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a privacy-relevant data analyzer scans through source code to detect privacy-relevant data, then data security and privacy protection are improved, but processor load and processing time increase
Solution Approach 1:
The source code is divided into discrete annotations that can be individually scanned and analyzed. The privacy-relevant data analyzer processes code segment by segment rather than analyzing the entire codebase at once, reducing processor load while maintaining comprehensive security coverage.
Solution Approach 2:
Annotations denoting privacy-relevant data are embedded in the source code during the development phase, before the scanning process occurs. This preliminary action prepares the data structure in advance, allowing the analyzer to quickly identify and process only relevant sections without examining every line of code, thereby reducing processing time and energy consumption.
2Reliability
If a privacy-relevant data analyzer scans through source code to detect privacy-relevant data, then data security and privacy protection are improved, but processing speed decreases
Solution Approach 1:
Annotations serve as intermediary markers in the source code that explicitly denote the presence of privacy-relevant data. Instead of scanning and analyzing every line of code to determine if it contains sensitive information, the analyzer simply searches for these pre-placed annotations, dramatically increasing processing speed while maintaining security detection accuracy.
Solution Approach 2:
The annotations are prepared in advance during code development, marking privacy-relevant data locations before the scanning process begins. This preliminary preparation allows the analyzer to quickly locate and process only the necessary portions of the code, improving processing speed without compromising security.
3Difficulty of detecting and measuring
If annotations are added to source code to denote privacy-relevant data, then ease of detection is improved, but device complexity increases
Solution Approach 1:
The source code becomes self-descriptive through the addition of annotations that automatically denote the presence of privacy-relevant data. The code structure serves its own detection needs by including these markers, eliminating the need for complex external analysis tools or manual review processes, thereby improving ease of detection without significantly increasing overall system complexity.
Data Source
AI summary
Systems and methods for protecting privacy-relevant data from unauthorized disclosure in source code of an application. For instance, the present disclosure provides a plurality of technical features including: a privacy-relevant data analyzer that analyzes source code, detects privacy-relevant data in the source code, and generates a report of instances of detected privacy-relevant data. In some examples, the privacy-relevant data analyzer scans through source code to detect annotations that denote if fields, records, or combinations thereof include privacy-relevant data. The privacy-relevant data analyzer further generates and provides a report of detected privacy issues associated with sensitive data included in source code so that the issues can be resolved to ensure that privacy is not breached.