Decision-Tree Security Event Quantification for Threat Prioritization
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Solution Overview
Problem
Current computer security tools lack the ability to effectively leverage information from multiple and disparate sources to mitigate against computer security attacks, failing to accurately analyze, quantify risk, generate remediative steps, and prioritize actions against security threats.
Innovation Solution
A system utilizing a decision tree to test security objects, linking nodes to security engines for threat analysis, which determines security threat parameters by classifying malware and assigning quantitative or qualitative vulnerability levels, and generating remediation strategies based on threat attributes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple security engines are used to analyze security objects from disparate sources, then measurement precision and reliability of threat detection improve, but device complexity increases
Solution Approach 1:
The system segments the security analysis function into multiple specialized security engines (e.g., malware detection engine, vulnerability assessment engine, threat intelligence engine), each responsible for analyzing specific aspects of security objects. This segmentation allows each engine to focus on particular threat types, improving detection precision while organizing complexity into manageable modular components.
Solution Approach 2:
The decision tree structure serves as a universal framework that coordinates multiple security engines, enabling a single system to handle diverse security objects (files, URLs, IPs, domains) and various threat types through a common analysis pathway. This multi-functional approach improves measurement precision across different security domains while providing a unified structure to manage system complexity.
2Reliability
If comprehensive threat analysis is performed using decision trees and multiple security engines, then reliability of security assessment improves, but loss of time in processing security objects increases
Solution Approach 1:
The system performs preliminary actions by pre-building decision trees with multiple nodes representing different analysis stages and security engines. When a security object arrives, the system traverses the pre-constructed decision tree, activating only the specific security engines relevant to the object type and observed characteristics. This preliminary structuring enables reliable comprehensive analysis while reducing processing time by avoiding unnecessary engine activations.
Solution Approach 2:
The decision tree mechanism enables partial action by selectively activating only the subset of security engines necessary for analyzing a given security object based on its type, attributes, and observed behavior. Rather than running all security engines on every object (excessive action), the system performs just enough analysis (partial action) to achieve reliable assessment, thereby reducing processing time while maintaining assessment reliability.
3Measurement precision
If security objects are tested through multiple analysis nodes and engines, then measurement precision of security parameters improves, but device complexity increases
Solution Approach 1:
The testing structure is segmented into discrete decision tree nodes, each associated with specific security engines and analysis functions. This segmentation allows precise measurement of security parameters by directing objects through targeted analysis paths, while organizing the testing complexity into modular, manageable node-engine associations that can be independently configured and maintained.
Data Source
AI summary
A system for testing a security object is disclosed. The system comprises processors and memory storing a plurality of security engines and instructions that, when executed by the processors, causes the system to: access a decision tree comprising a first node and a plurality of second nodes; link a first leaf node of the decision tree with a first security engine; link a second leaf node of the decision tree with a second security engine; receive a security object comprising a digital asset that is attackable using one or more attack execution operations; and test the security object using the decision tree to determine a security threat parameter for the security object. The security threat parameter may be used to prioritize one or more remediation steps for mitigating against the one or more attack execution operations associated with the digital asset.