Shared Document Protection via Sensitive Content Redaction
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Solution Overview
Problem
Existing systems fail to effectively prevent unauthorized access and display of sensitive information within search results and linked documents, leading to potential data breaches and security risks, while consuming excessive computing resources.
Innovation Solution
A permissions-aware search and knowledge management system that automatically detects sensitive information and adjusts access control lists, performs content redactions, and disables links to documents when shared with unauthorized users, leveraging deep learning models for personalized search results and reduced resource consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the search system continuously scans and monitors all documents for sensitive information, then data security is improved, but computing resource consumption increases
Solution Approach 1:
The system performs preliminary classification and tagging of documents during the indexing phase, identifying potentially sensitive documents before they are shared. This preliminary action allows the system to focus continuous monitoring only on high-risk documents rather than all documents, reducing computing resource consumption while maintaining data security.
Solution Approach 2:
Documents automatically tag themselves with sensitivity classifications and access control metadata during the indexing process. This self-service mechanism eliminates the need for manual sensitivity assessment and reduces the computational burden on the search system during scanning operations.
2Reliability
If the system automatically adjusts access control lists and performs content redactions, then unauthorized access is prevented, but system complexity increases
Solution Approach 1:
The system merges the access control list management and content redaction functions into a single automated protection module. This consolidation reduces system complexity by eliminating redundant components while maintaining the effectiveness of unauthorized access prevention through coordinated execution of both functions.
Solution Approach 2:
An intermediary protection module is introduced between the search system and document storage, which automatically handles access control adjustments and content redactions. This intermediary layer simplifies the overall system architecture by centralizing security operations and isolating complexity from both the user interface and core search functionality.
3Reliability
If the system disables links to shared documents with sensitive information, then data breach risks are reduced, but information accessibility for authorized users decreases
Solution Approach 1:
The system applies different link protection strategies based on the local characteristics of each document and user. Authorized users with proper permissions experience no disruption to information accessibility, while unauthorized users encounter disabled links. This localized quality approach ensures data breach prevention without compromising ease of operation for legitimate users.
Solution Approach 2:
The system dynamically changes the accessibility parameter of document links based on real-time assessment of user authorization and document sensitivity. Links are not permanently disabled but rather have their access parameters adjusted conditionally, allowing authorized users to access information while preventing data breaches from unauthorized access.
Data Source
AI summary
Methods and apparatuses for preventing the unauthorized use and display of sensitive information in shared documents are described. A method includes performing a scan on a shared document to identify sensitive information in the shared document, determining, based on an exposure level of the shared document, a security action to be applied to the shared document to protect the sensitive information, and performing the security action to restrict access to at least a portion of the sensitive information.