Incident Response Ontology for Signal Prioritization
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Solution Overview
Problem
Current incident response systems are hindered by delays and inefficiencies due to disconnected information sources and lack of synchronization, leading to ineffective and delayed responses to incidents, as they struggle to distinguish between signal and noise in the vast amount of real-time data generated.
Innovation Solution
An end-to-end computing system that integrates information from various sources, generates an ontological representation of incidents, and determines a tiered response mechanism based on inferred exigency, enabling synchronized contextualization and targeted response implementation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If real-time data is acquired from multiple sources, then awareness of incidents is improved, but the ability to distinguish signal from noise deteriorates due to data volume and lack of synchronization
Solution Approach 1:
The patent merges multiple disconnected information sources into a unified incident response system. The system integrates data from diverse sources including social media, news feeds, sensor networks, and internal systems, synchronizing them through a common temporal and spatial reference framework. This consolidation enables centralized processing and analysis that distinguishes relevant incident signals from noise through coordinated multi-source validation.
Solution Approach 2:
The patent introduces an intermediary incident response system that acts as a mediator between raw data sources and response actions. This intermediary layer includes components for data normalization, temporal alignment, spatial contextualization, and priority scoring. The system mediates the flow of information by filtering, correlating, and prioritizing data before presenting it to decision-makers, thereby enabling signal detection amidst voluminous multi-source data.
2Device complexity
If information sources are disconnected and siloed, then system simplicity is maintained, but response effectiveness deteriorates due to delays in identifying relevance and deploying responses
Solution Approach 1:
The patent merges previously disconnected information sources and response mechanisms into an integrated incident response system. The system combines data acquisition from multiple external and internal sources with contextual information, analysis capabilities, and response deployment functions into a unified architecture. This integration eliminates silos and enables seamless information flow from detection to response action.
Solution Approach 2:
The patent creates a universal incident response system that performs multiple functions through a single integrated platform. The system simultaneously acquires data from diverse sources, normalizes different data formats, contextualizes information spatially and temporally, analyzes incident patterns, prioritizes responses, and deploys actions across multiple channels. This multi-functional approach replaces multiple specialized systems with one versatile incident response platform.
3Speed
If real-time data synchronization is not implemented, then data acquisition speed is maintained, but the ability to leverage real-time data deteriorates due to delays in analysis and response deployment
Solution Approach 1:
The patent implements preliminary actions by pre-establishing a synchronized reference framework before incident analysis begins. The system pre-configures temporal alignment mechanisms, spatial contextualization rules, and data normalization templates. These preliminary structures enable immediate processing of incoming real-time data without requiring complex synchronization operations during active incident response, thereby maintaining acquisition speed while eliminating analysis delays.
Data Source
AI summary
Computing systems methods, and non-transitory storage media are provided for obtaining information regarding an incident, generating a representation of the information, augmenting the representation with additional contextual information, determining a response to address the incident, and implementing the response or transmitting the determined response to a separate computing system that implements the response.