Virtual Machine File Behavior Analysis for Rapid Virus Detection
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Solution Overview
Problem
Traditional computer virus detection methods are slow to detect and react to new threats, allowing viruses to cause harm before detection, and often consume significant system and network resources, making systems vulnerable during the delay.
Innovation Solution
A method that involves analyzing file changes by executing them in a virtual machine, comparing resulting behavior to indicative patterns, and handling the file as potentially infected if the behavior matches that of another file, allowing for rapid identification and mitigation of viruses without relying on external signature data sets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional signature-based virus detection is used, then detection accuracy for known viruses is improved, but reaction time to new threats deteriorates and system resources are consumed
Solution Approach 1:
The system performs preliminary analysis of file changes by executing them in a virtual machine before allowing actual execution. This advance detection mechanism analyzes behavioral patterns and compares them against known virus indicators, enabling the system to identify threats before they can cause harm, thus reducing reaction time while maintaining detection accuracy
Solution Approach 2:
A virtual machine serves as an intermediary environment between the user's system and potentially malicious files. The VM executes suspicious files in isolation, allowing the detection system to observe behavioral patterns without risking the host system. This intermediary approach enables rapid analysis of new threats while protecting system resources
2Reliability
If traditional centralized signature distribution is used, then detection capability is maintained, but network resource consumption increases and update delays occur
Solution Approach 1:
The detection system performs self-service by maintaining local behavioral pattern databases and executing analysis independently within the virtual machine environment. Instead of continuously requesting signature updates from centralized servers, the system autonomously analyzes file changes and compares them against stored behavioral indicators, significantly reducing network resource consumption while maintaining reliable detection capability
Solution Approach 2:
The detection system segments the virus detection function into independent behavioral analysis modules that operate locally. Rather than relying on a single centralized signature database, the system divides detection capabilities across multiple local behavioral pattern sets, allowing parallel analysis of different file attributes and reducing the need for frequent network updates
3Productivity
If virtual machine execution analysis is performed, then detection speed for new threats is improved, but system resource consumption increases
Solution Approach 1:
The system applies partial action by selectively analyzing only specific behavioral patterns and file attributes within the virtual machine, rather than performing exhaustive analysis of all file operations. The detection process focuses on key indicators such as system calls, file access patterns, and execution behavior, enabling rapid detection of new threats while consuming fewer system resources than complete analysis would require
Data Source
AI summary
Systems and methods for computer virus detection are presented. In one embodiment; an computer virus detection method includes: receiving an indication of a change to a file; performing a virus analysis process, including executing the changes to the file in a virtual machine and examining results of the executing the changes; and handling the file based upon the virus analysis. The virus analysis can be performed in a system in which the change to the file occurs. Handling the file can include treating the file as potentially infected with a virus based upon the virus analysis. In one exemplary implementation, examining the results includes comparing the results of executing the changes to the file to other results from executing changes to another file, wherein the file is identified as potentially infected with a virus if the examining results indicates the results of executing the changes to the file are similar to results from executing changes to another file. Examining results includes examining behavior resulting from executing the file (e.g., examining system calls, etc.). Outcome of the examining results can be forwarded for utilization in developing virus data sets.