Context-Aware DXL Broker for Threat Intelligence Sharing
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Solution Overview
Problem
In the context of enterprise security, existing systems face challenges in real-time threat intelligence sharing and malware management due to heterogeneous software ecosystems, disparate data representations, and lack of a unified threat intelligence repository, leading to inefficiencies in malware detection and response across autonomous network elements.
Innovation Solution
A context-aware network utilizing a data exchange layer (DXL) that enables real-time, bi-directional communication and data reconciliation across network elements, providing a unified framework for threat intelligence sharing and adaptive security decisions through a publish-subscribe messaging infrastructure and domain master functionality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a unified threat intelligence repository is implemented, then threat intelligence sharing efficiency is improved, but system complexity increases
Solution Approach 1:
The patent implements a Data Exchange Layer (DXL) broker as an intermediary component that mediates between autonomous network elements and the threat intelligence repository. The broker handles authentication, message routing, and data reconciliation, thereby improving threat intelligence sharing efficiency while isolating the complexity of the unified repository from individual network elements.
Solution Approach 2:
The system architecture is segmented into distinct functional components: autonomous network elements, DXL broker, and the unified threat intelligence repository. This segmentation allows each component to operate independently with well-defined interfaces, improving overall system efficiency while managing complexity through modular design.
2Loss of time
If real-time communication across network elements is enabled, then malware detection latency is reduced, but data consistency challenges increase
Solution Approach 1:
The DXL broker implements feedback mechanisms where network elements publish security events in real-time, and the broker reconciles data from multiple sources before distributing updated threat intelligence back to the network. This closed-loop feedback system enables rapid detection while maintaining data consistency through centralized coordination.
Solution Approach 2:
The system performs preliminary data reconciliation and validation at the broker level before distributing threat intelligence to network elements. This preliminary action ensures data consistency is established in advance, allowing real-time communication without propagating inconsistent data.
3Measurement precision
If heterogeneous data representations are standardized, then data reconciliation accuracy is improved, but integration complexity increases
Solution Approach 1:
The DXL broker implements universal data representation standards that enable it to handle multiple data formats from heterogeneous network elements. The broker provides multi-functional capabilities to translate, validate, and reconcile various data representations against a unified schema, improving reconciliation accuracy while centralizing integration complexity within the broker.
Data Source
AI summary
There is disclosed in one example a data exchange layer (DXL) broker, including: a hardware platform including a processor; and instructions encoded in a memory to instruct the processor to communicatively couple to a DXL fabric configured to operate a one to-many (1:N, N>1) publish-subscribe fabric; provide an interface to authenticate and register DXL endpoints with the DXL broker; and provide DXL messaging, including maintaining a routing table of registered DXL endpoints; receiving from a first registered DXL endpoint a one-to-one (1:1) request for an endpoint of the DXL fabric, wherein the endpoint is not a registered DXL endpoint of the broker; and publishing the 1:1 request to the DXL fabric.