Threat Event Lineage Lookup Using Data Lake Time Partitions
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Solution Overview
Problem
Existing systems lack effective tools for visualizing threat development in enterprise networks and managing security events to facilitate immediate detection, investigation, and disposal of potential threats.
Innovation Solution
A threat management system that creates a lineage for security events on compute instances, including process identifiers and timestamps, which are transmitted to a threat management facility for immediate visualization and augmented with additional data from a data lake, enabling rapid threat timeline visualization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If additional data is retrieved from the data lake to augment the lineage, then the completeness and accuracy of threat analysis is improved, but the time required for visualization and analysis increases
Solution Approach 1:
The system performs preliminary actions by pre-partitioning the data lake into time-based segments and pre-processing event data for rapid retrieval. When a security event is detected, the system already has the lineage structure ready with timestamps, allowing it to quickly locate and retrieve only the necessary augmented data from the appropriate time partitions without scanning the entire data lake, thus reducing query time while maintaining data completeness.
Solution Approach 2:
The data lake is segmented into temporal partitions based on time windows, allowing the system to retrieve only the relevant data segments needed for a specific security event investigation. This segmentation enables parallel data retrieval operations and reduces the amount of data that needs to be processed, thereby decreasing the time required to augment lineage data while preserving analytical accuracy.
2Loss of information
If the lineage is progressively updated as additional information becomes available, then the completeness of threat information is improved, but the complexity of data management and retrieval increases
Solution Approach 1:
The system implements feedback mechanisms where the threat management facility monitors data availability and user requests, progressively augmenting the lineage visualization as additional information becomes available. The system receives feedback from data lake queries and dynamically updates the visualization, ensuring completeness while managing complexity through structured update protocols and cached data structures that track what information has been retrieved and what remains to be fetched.
Solution Approach 2:
The system prepares preliminary lineage structures with placeholder information and ready-to-fetch data schemas before complete information is available. This allows the visualization to be immediately displayed with core event details while the framework is pre-configured to automatically retrieve and integrate additional contextual information from the data lake as it becomes available, reducing the perceived complexity of progressive updates.
3Quantity of substance
If event data is stored in a data lake for long-term storage, then the capacity to retain historical security data is improved, but the speed of data retrieval for immediate visualization decreases
Solution Approach 1:
The data lake is segmented into time-based partitions, allowing the system to retrieve only the specific time window data needed for immediate visualization of recent security events. This segmentation enables the system to maintain vast historical data capacity while achieving fast retrieval speeds by querying only relevant temporal segments rather than scanning the entire data lake, thus resolving the contradiction between data retention capacity and retrieval speed.
Solution Approach 2:
The system introduces an intermediary layer between the data lake and the visualization interface, consisting of a threat management facility that acts as a mediator. This intermediary pre-processes, indexes, and caches data from the data lake, creating a buffer that enables fast retrieval of recent event data for immediate visualization while the data lake continues to store comprehensive historical data. The intermediary handles the complexity of rapid data access patterns.
Data Source
AI summary
A threat management facility for an enterprise network provides visualization tools for threat analysis and investigation. While security events may generally be logged in a long term data repository such as a data lake, security events can be transmitted directly to a short term, higher performance data repository for faster visualization when fast response times might be necessary or helpful. In this context, the threat management facility may use time stamps associated with event reporting to select a time-indexed segment of the data lake as a target for supplemental, investigative queries.