Indexed Breach Detection for Multi-Source Node Isolation
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Solution Overview
Problem
Data breaches often go undetected for extended periods due to their occurrence across multiple data sources, making timely mitigation difficult and increasing the negative consequences.
Innovation Solution
A breach detection engine that crawls data sources, generates an index, and queries it using keywords to identify potential breaches, computes likelihood using breach criteria weights, and isolates network nodes associated with breaches to perform remedial actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If data breaches are monitored across multiple data sources manually, then detection accuracy may be maintained, but detection time increases significantly and mitigation is delayed
Solution Approach 1:
The patent segments the monitoring task by dividing it into modular components: crawling module for data collection, indexing module for organization, query module for breach detection, and mitigation module for response. Each module handles a specific aspect of breach detection across multiple data sources, enabling parallel processing and reducing overall detection time while maintaining manageable complexity through modular architecture
Solution Approach 2:
The patent creates a universal breach detection system that can monitor multiple types of data sources (databases, file systems, cloud storage) using the same core architecture. The system uses standardized indexing and querying mechanisms that work across different data formats and sources, eliminating the need for separate manual monitoring processes for each source and significantly reducing detection time
2Productivity
If automated breach detection systems are implemented, then detection speed increases, but false positives increase and require manual verification
Solution Approach 1:
The patent implements feedback mechanisms where query results are analyzed and weighted based on multiple criteria (data sensitivity, breach indicators, source reliability). The system adjusts its detection thresholds and weighting schemes based on historical data and confirmed breaches, improving accuracy over time while maintaining high detection speed through automated feedback loops that reduce false positives
Solution Approach 2:
The patent changes detection parameters dynamically based on the specific data source and context. Different data sources have different sensitivity thresholds and breach indicators. The system adjusts query parameters, weighting factors, and detection criteria based on the type of data being monitored, enabling fast automated detection while maintaining high precision by adapting to each specific context
3Measurement precision
If comprehensive breach criteria are used to compute likelihood, then detection accuracy improves, but computational complexity and processing time increase
Solution Approach 1:
The patent applies partial action by implementing a two-stage detection process: first a quick initial assessment using key breach indicators, then a more comprehensive analysis only for suspicious cases. This allows the system to maintain high detection accuracy for critical breaches while reducing computational overhead by applying full criteria only when necessary, optimizing the balance between precision and resource usage
Solution Approach 2:
The patent performs preliminary indexing and categorization of data during the crawling phase, organizing information in advance to enable faster querying and analysis. By pre-processing and structuring data beforehand, the system reduces the computational burden during actual breach detection, maintaining high accuracy through comprehensive criteria while minimizing real-time computational resource consumption
Data Source
AI summary
A breach detection engine detects and mitigates the effects of breaches across one or more data sources. An index is generated based on one or more data sources and the index is queried using keywords indicative of potential breaches. A database of potential breaches is populated based on the query of the index. The potential breach database is queried using keywords associated with a system identity (e.g., a third party). A likelihood of a candidate breach is identified based on a set of breach criteria weights. A network node associated with a candidate breach determined to be an actual breach is identified for isolation or for the performance of one or more additional security actions.