Memory Dump Sensitive Data Redaction via Tagging
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Solution Overview
Problem
Computer systems face challenges in protecting sensitive user data during memory dumps, as unauthorized access can lead to legal repercussions, fraud, and loss of consumer trust due to the inability to effectively redact sensitive information.
Innovation Solution
A system and method that utilize memory tagging and a sensitive data identification module to identify and redact sensitive data in memory dumps, employing machine learning models and API calls to tag and encrypt sensitive data, ensuring that only non-sensitive data is included in the redacted dump.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If memory dumps include all data for diagnostic purposes, then diagnostic completeness is improved, but sensitive data exposure risk increases
Solution Approach 1:
The patent extracts sensitive data from memory dumps by identifying tagged memory pages containing sensitive information and removing or redacting them from the final dump output. This allows the dump to retain diagnostic value while eliminating exposure risks.
Solution Approach 2:
The system performs preliminary tagging of memory pages as sensitive before the dump is generated. This advance identification allows the dumping module to automatically exclude or redact marked pages, preventing sensitive data exposure before it can occur.
2Reliability
If sensitive data is redacted from memory dumps, then data privacy protection is improved, but diagnostic accuracy may deteriorate
Solution Approach 1:
The patent segments memory into distinct tagged pages, allowing selective redaction of only those pages marked as sensitive. Non-sensitive pages retain their full diagnostic content, preserving overall diagnostic accuracy while protecting privacy.
Solution Approach 2:
Different quality treatment is applied to different memory pages: sensitive pages are redacted or removed, while non-sensitive pages are preserved in full. This localized approach ensures privacy protection where needed without compromising diagnostic information elsewhere.
3Reliability
If manual review of memory dumps is performed to protect sensitive data, then data security is improved, but processing time increases
Solution Approach 1:
The system performs automatic identification and redaction of sensitive data through the dumping module working with tagged memory pages. This self-service approach eliminates the need for manual review while maintaining data security, significantly reducing processing time.
Solution Approach 2:
Memory pages are pre-tagged as sensitive before the dump process, enabling the dumping module to automatically identify and redact them without manual intervention. This preliminary marking streamlines the entire process while ensuring security.
Data Source
AI summary
Examples of techniques for sensitive data redaction in a memory dump are described herein. An aspect includes, based on a dump of a virtual address space being triggered, receiving a primary dump corresponding to the virtual address space, the primary dump including one or more tagged memory pages. Another aspect includes identifying, by a sensitive data identification module, sensitive data that is located outside of the of the one or more tagged memory pages in the primary dump. Another aspect includes redacting data corresponding to the sensitive data and the one or more tagged memory pages to determine a redacted dump.