Multi-Channel Data Fusion for Cybersecurity Vulnerability Detection
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Solution Overview
Problem
Current cybersecurity monitoring architectures are limited in their ability to provide comprehensive insights into security vulnerabilities across multiple data planes and require separate cataloging of computer assets, leading to missed vulnerabilities due to incomplete asset identification, which can result in undetected cybersecurity threats and attacks.
Innovation Solution
A multi-channel data fusion system that integrates device connectivity data from various sources to identify vulnerabilities, assign them to specific cybersecurity dimensions, and generate multi-dimensional risk scores, enabling proactive detection and remediation through a user-interactive dashboard.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing cybersecurity monitoring architectures focus on a particular data plane, then monitoring depth for that specific plane is improved, but vulnerability detection coverage across multiple data planes deteriorates
Solution Approach 1:
The patent combines multiple data channels (network data, infrastructure data, application data, asset data) into a unified cybersecurity monitoring system. The processing circuit integrates data from these separate channels to comprehensively identify vulnerabilities across all data planes, resolving the contradiction between monitoring depth and coverage by merging previously separate monitoring functions into a cohesive multi-dimensional system.
2Reliability
If separate cataloging of computer assets is required, then asset tracking for monitored planes is improved, but asset identification completeness across all planes deteriorates
Solution Approach 1:
The patent creates a universal asset cataloging system that handles multiple types of assets across different data planes simultaneously. The processing circuit identifies and catalogs various asset types (network assets, infrastructure assets, application assets, device assets) through a single multi-functional system, eliminating the need for separate cataloging processes for each data plane and improving overall asset identification completeness.
3Productivity
If cybersecurity monitoring is limited to particular data planes, then monitoring efficiency for those planes is improved, but vulnerability detection timeliness deteriorates
Solution Approach 1:
The patent implements preliminary action by continuously collecting and preprocessing data from multiple channels in advance, maintaining updated asset catalogs and vulnerability databases ready for analysis. When security events occur, the system can immediately correlate them with pre-collected data from all data planes, enabling timely vulnerability detection without the delay of sequential data gathering from separate monitoring systems.
Data Source
AI summary
Systems, methods, and computer-readable storage media are utilized to analyze multi-channel data based on a security model in a computer network environment. One system includes a plurality of data channels configured to access entity data and a processing circuit communicatively coupled to a data channel of the plurality of data channels, the processing circuit configured to identify at least one vulnerability, determine an impact of the at least one vulnerability, assign the first property to a first cybersecurity dimension, generate a cybersecurity risk score based at least on the impact of the at least one vulnerability, and generate a multi-dimensional score for a target computer network environment based on the cybersecurity risk score.