Threat Detection via Behavioral Profiling and Vulnerability Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current malware detection methods rely on recognizing known patterns and are ineffective against previously unknown threats, failing to provide early detection and protection against emerging malicious software.
Innovation Solution
A system that analyzes computer systems for common vulnerability types and misconfigurations, monitors application behavior, and creates profiles to identify deviations from expected behavior, allowing for the detection and classification of malicious or suspicious applications or services before they cause harm.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional malware detection methods relying on known patterns are used, then detection of known threats is effective, but detection of previously unknown threats is impossible
Solution Approach 1:
The system performs preliminary actions by creating behavioral profiles of applications during their normal operation before malware infection occurs. These profiles capture expected behavior patterns that serve as a baseline for future comparison, enabling detection of deviations that indicate malware activity even before the malware exists in the wild.
Solution Approach 2:
The system implements feedback by continuously monitoring application behavior and comparing it against the pre-established behavioral profiles. When deviations are detected, the system provides feedback through alerts and responses, creating a closed-loop detection mechanism that adapts to new threats by learning from observed behaviors.
2Adaptability or versatility
If behavioral monitoring of all applications is performed, then unknown threats can be detected, but system complexity and resource consumption increase
Solution Approach 1:
The system applies local quality by focusing monitoring resources on specific applications that exhibit vulnerability types or misconfigurations rather than uniformly monitoring all applications. This selective approach reduces system complexity while maintaining high detection capability for high-risk applications.
Solution Approach 2:
The system changes parameters by dynamically adjusting monitoring intensity and profile creation based on application characteristics, vulnerability types, and risk levels. This allows the system to optimize resource allocation and reduce complexity by applying different monitoring strategies to different applications based on their specific parameters.
3Loss of time
If vulnerability analysis and behavioral profiling are combined, then early detection of unknown threats is enabled, but analysis time and computational resources increase
Solution Approach 1:
The system performs vulnerability analysis and creates behavioral profiles during application installation and normal operation, before any malware infection occurs. This preliminary action allows the system to have detection capabilities ready in advance, enabling rapid detection of unknown threats without requiring intensive computational resources at the moment of threat detection.
Data Source
AI summary
There is provided a method of detecting a threat against a computer system. The method comprises: creating a modular representation of behavior of known applications on the basis of sub-components of a set of known applications; entering the modular representation to an evolutionary analysis system for generating previously unknown combinations of the procedures; storing the generated previously unknown combinations as candidate descendants of known applications to a future threat candidate database; monitoring the behavior of the computer system to detect one or more procedures matching the behavior of a stored candidate descendant in the future threat candidate database; and upon detection of one or more procedures matching the behavior of the stored candidate descendant and if the stored candidate descendant is determined to be malicious or suspicious, identifying the running application as malicious or suspicious.