Ransomware Detection via File Write Entropy Analysis
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Solution Overview
Problem
Current methods fail to effectively detect ransomware attacks in real-time before data and files are completely encrypted, leading to potential permanent loss or costly decryption processes.
Innovation Solution
A method involving monitoring file write operations, calculating entropy values, and comparing them to predetermined thresholds to flag potentially encrypted files by ransomware, along with extracting and analyzing memory regions for cryptographic artifacts to identify and decrypt affected files.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional malware detection methods are used, then detection capability is limited, but real-time detection before complete encryption cannot be achieved
Solution Approach 1:
The patent performs preliminary analysis of file write operations by calculating entropy values and checking for cryptographic artifacts in memory buffers before the ransomware completes encryption. This early detection mechanism allows the system to identify potential ransomware attacks during the initial file write stage, preventing complete encryption and enabling timely intervention.
Solution Approach 2:
The patent replaces traditional signature-based detection mechanisms with an entropy-based detection system. By substituting the mechanical approach of comparing file signatures against known malware databases with a mathematical entropy analysis of file write operations, the system achieves real-time detection capability without being limited by prior knowledge of specific ransomware variants.
2Reliability
If complete file encryption occurs before detection, then data loss is permanent, but early detection requires analyzing file write operations in real-time
Solution Approach 1:
The patent extracts only the critical portion of file data (the first 64 bytes written to the memory buffer) for entropy analysis, rather than analyzing entire files. This extraction approach enables real-time detection with minimal computational overhead, maintaining data protection reliability while avoiding the complexity of analyzing complete files in real-time.
Solution Approach 2:
The patent changes the detection parameter from traditional malware signature matching to entropy value calculation. By monitoring the entropy of data in memory buffers during file write operations, the system achieves reliable ransomware detection with simple computational operations, avoiding the complexity of maintaining and updating extensive malware signature databases.
3Measurement precision
If entropy calculation is performed on large files, then detection accuracy improves, but processing time and computational resources increase
Solution Approach 1:
The patent applies partial action by calculating entropy only on the first 64 bytes of file data written to the memory buffer, rather than processing entire files. This partial analysis provides sufficient detection accuracy for ransomware identification while dramatically reducing computational resource consumption compared to full-file entropy calculation.
Data Source
AI summary
The present invention relates to a computer program product, a computing device and a method of detecting a file encrypted by ransomware by identifying a file write operation for a file on the computing device and determining if a predetermined number of bytes of the file is stored in a memory buffer on the computing device. An entropy value of the predetermined number of bytes in the memory buffer is determined and compared to a first predetermined threshold, wherein if the determined entropy value exceeds the first predetermined threshold the file associated with the file write operation is flagged as being potentially encrypted by ransomware.