Threat Correlation via Multi-Streaming Data Service
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Solution Overview
Problem
Current computer security systems face challenges in scalable and real-time correlation of security threat information across network components, often relying on human analysts and vendor products that are not scalable or efficient in responding to potential threats.
Innovation Solution
A multi-streaming data service that elastically scales to distribute security threat information in parallel to multiple network components, correlating threat data from various sources, including network components, external agencies, and databases, to enable low-latency identification and response to security threats.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional security systems use vendor products and human analysts for threat correlation, then security analysis can be performed, but scalability and response efficiency deteriorate
Solution Approach 1:
The system enables network components to autonomously execute security policies and respond to threats without requiring human analyst intervention. The automated correlation engine self-manages the entire threat detection and response process, allowing the system to scale without additional human resources while maintaining high productivity in threat correlation.
2Loss of time
If security threat information is correlated in real-time across multiple network components, then response latency is reduced, but system complexity increases
Solution Approach 1:
The correlation system is segmented into distributed correlation engines deployed across multiple network components rather than a centralized system. Each engine handles local threat correlation independently, reducing communication overhead and latency while distributing system complexity across multiple manageable units rather than one complex centralized system.
Solution Approach 2:
The correlation engine is designed as a multi-functional component that can correlate threats across different network components, data types, and security policies simultaneously. This universal design reduces overall system complexity by using a single versatile correlation mechanism rather than multiple specialized systems.
3Reliability
If security threat information is distributed to multiple network components, then threat response capability is improved, but data management complexity increases
Solution Approach 1:
The system implements feedback mechanisms where network components report threat detections and policy execution results back to the correlation engine. This feedback loop enables automated adjustment of correlation rules and policy enforcement, improving threat response capability while reducing data management complexity through self-regulating feedback control rather than manual management.
Data Source
AI summary
A computer security threat sharing technology is described. An example method may include receiving security threat information transmitted over a computing network via a multi-streaming data service. The security threat information may relate to a recognized computer security threat detected by a first network component. The security threat information may then be correlated with additional security threat information received via the multi-streaming data service that may be detected by a second network component that may be interconnected to the first network component by way of the multi-streaming data service. A computer security threat associated with correlated security threat information may then be identified, and the computer security threat may be communicated to a plurality of network components via the multi-streaming data service.