Incident Response Tool Using Data Exchange Layer
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Solution Overview
Problem
Current incident response tools for computer systems are slow and inefficient in identifying and isolating problems on user devices, requiring significant time and resources, especially in large-scale networks.
Innovation Solution
A data exchange layer system that enables real-time, bi-directional communication between devices, utilizing proactive incident response traps, local history caches, and baseline generation to quickly detect and respond to incidents across hundreds of thousands or millions of user devices, reducing operational overhead and improving response speed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional incident response tools are used to identify and isolate problems on user devices, then comprehensive problem detection is achieved, but significant time and resources are required
Solution Approach 1:
The system performs preliminary actions by continuously collecting and caching diagnostic data from user devices before incidents occur. Local history caches store baseline information about normal device operations, enabling rapid comparison when incidents are detected without requiring time-consuming data collection during the incident response phase.
Solution Approach 2:
The incident response system is segmented into multiple independent components: data collectors on user devices, local history caches, baseline generators, and incident response engines. This segmentation allows parallel processing of multiple devices and incidents simultaneously, reducing overall response time while maintaining comprehensive detection capabilities.
2Reliability
If traditional incident response tools are deployed across large-scale networks, then comprehensive security monitoring is achieved, but operational overhead increases significantly
Solution Approach 1:
User devices perform self-service by automatically collecting and caching their own diagnostic data locally. Each device maintains its own history cache and baseline information, eliminating the need for centralized data collection from every device. This self-service approach maintains comprehensive security monitoring while dramatically reducing network overhead and operational complexity.
Solution Approach 2:
The system performs preliminary data collection and caching actions at each device locally, so that when incidents occur, the diagnostic information is already available without requiring complex centralized coordination. This preliminary action simplifies the operational overhead for large-scale deployments while maintaining reliable security monitoring coverage.
3Speed
If real-time data collection is implemented across hundreds of thousands of devices, then rapid incident detection is achieved, but network bandwidth and processing resources are consumed
Solution Approach 1:
Diagnostic data is collected and cached locally on each user device in advance, creating a local history cache that stores baseline information about normal operations. This preliminary action eliminates the need for continuous real-time data transmission across the network, achieving rapid incident detection through local comparisons while minimizing network bandwidth consumption.
Solution Approach 2:
The system segments data processing by performing baseline generation and incident detection locally at each device rather than centralizing all processing. This segmentation allows each device to independently detect incidents using its own cached data, achieving fast detection speed while distributing processing resources and minimizing network energy consumption.
Data Source
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AI summary
This disclosure describes systems, methods, and computer-readable media related to an incident response tool using data exchange layer. In some embodiments, a data collector may be generated by an incident response server. The incident response server may transmit a data collector to multiple broker servers, where each broker server may transmit the data collector to multiple user devices associated with the broker server. The incident response server may receive data from the data collectors executing on the user devices and may analyze the received data.