Malware Analysis System Using Virtual Machine Behavior Profiling
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Solution Overview
Problem
Current firewalls are ineffective in detecting zero-day malware threats due to the lack of preexisting signatures, and existing solutions either fail to prevent infections or are overly restrictive, lacking the ability to automatically generate and distribute new signatures in real-time.
Innovation Solution
A malware analysis system utilizing a virtual machine for behavior profiling and heuristic-based analysis to detect and generate new signatures for zero-day threats, which are then distributed to network devices to block future infections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If firewalls use preexisting signatures to detect malware, then detection accuracy is improved, but inability to detect zero-day threats occurs
Solution Approach 1:
The system performs preliminary behavior analysis on suspected malware files by executing them in an isolated virtual environment before they can cause harm. This preliminary action allows the system to observe malicious behaviors and generate signatures in advance, enabling detection of zero-day threats without relying on preexisting signatures.
Solution Approach 2:
The firewall system automatically analyzes suspicious files, generates new signatures based on observed malicious behaviors, and updates its own signature database without external intervention. This self-service capability enables real-time adaptation to new threats while maintaining protection against known malware through preexisting signatures.
2Reliability
If firewalls block all unknown traffic to prevent infections, then security is improved, but network usability deteriorates
Solution Approach 1:
Instead of blocking all unknown traffic, the system applies partial action by only blocking traffic identified as malicious through behavior analysis. Files are executed in an isolated environment and only those demonstrating malicious behaviors are blocked, while legitimate unknown traffic is permitted to pass through normally.
Solution Approach 2:
The system introduces an intermediary virtual execution environment between the network and the protected system. Suspected malware is analyzed in this intermediate environment, allowing the system to distinguish between malicious and legitimate traffic without directly blocking network communications, thus maintaining usability while ensuring security.
3Measurement precision
If manual analysis of malware samples is performed, then detection accuracy is improved, but response time deteriorates
Solution Approach 1:
The system automatically performs behavior analysis on suspected malware files by executing them in an isolated virtual environment and generating signatures based on observed malicious behaviors. This automated self-service process eliminates manual analysis steps while maintaining high detection accuracy, enabling real-time response to threats without time loss.
Solution Approach 2:
The system performs preliminary automated behavior analysis on suspicious files as they are intercepted, generating signatures before the files can execute or cause harm. This preliminary action reduces response time by eliminating delays associated with manual analysis while maintaining accurate threat detection through comprehensive behavior observation.
Data Source
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AI summary
In some embodiments, a malware analysis system includes receiving a potential malware sample from a firewall; analyzing the potential malware sample using a virtual machine to determine if the potential malware sample is malware; and automatically generating a signature if the potential malware sample is determined to be malware. In some embodiments, the potential malware sample does not match a preexisting signature, and the malware is a zero-day attack.