Early Malware Detection Using Sequential Endpoint Attack Patterns
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Solution Overview
Problem
Existing network security tools struggle to detect sustained and targeted malware attacks across a large and complex network attack surface, failing to provide early warning of potential breaches despite successful defense of individual incidents.
Innovation Solution
A system that identifies patterns of sequential malware tool usage across multiple endpoints, grouping indicators of breach to detect progressive deployment of malware, particularly for ransomware attacks, and notifies customers of potential breaches.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional network security tools are used to detect individual malware incidents, then individual attack detection capability is improved, but ability to detect sustained targeted attacks across the entire network deteriorates
Solution Approach 1:
The patent combines multiple individual malware detection results into a unified analysis framework that evaluates sequential patterns across the entire network. By merging isolated detection events into a comprehensive attack narrative, the system detects sustained targeted attacks that individual tools would miss.
Solution Approach 2:
The patent adds a temporal and sequential dimension to malware detection by analyzing the order and progression of different malware tools across multiple endpoints. This transforms detection from a static, single-point analysis to a dynamic, multi-dimensional pattern recognition system.
2Area of stationary object
If security monitoring is implemented across the entire network, then comprehensive attack surface coverage is improved, but complexity of detection and analysis deteriorates
Solution Approach 1:
The patent segments the complex network attack surface into manageable components by analyzing malware detections at individual endpoints first, then progressively combining these segments into broader attack patterns. This hierarchical segmentation makes comprehensive monitoring tractable.
Solution Approach 2:
The patent introduces an intermediary analysis layer that processes raw malware detection data from multiple endpoints and transforms it into meaningful attack patterns. This intermediary layer simplifies the complexity by providing structured intermediate representations that bridge raw data and final conclusions.
3Reliability
If reactive security response is used after breach detection, then individual incident response is improved, but proactive prevention of sustained attacks deteriorates
Solution Approach 1:
The patent performs preliminary analysis of malware detection patterns to identify early signs of sustained attacks before they result in successful breaches. By taking preliminary action on detected patterns, the system provides advance warning and enables proactive prevention rather than reactive response.
Data Source
AI summary
Malware detections are received from a plurality of endpoints in one or more enterprise networks. A first and second set of indicators of breach may be identified from the malware detections and, where appropriate, grouped by specific customers. The pattern of progressive deployment of malware directed toward a customer can then be used as a basis for identifying generalized targeting of the customer, or extended staging for a specific attack on the customer such as a ransomware attack.