Virtual File Honeypots for Detecting Injected Ransomware Threads
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Solution Overview
Problem
Conventional file honeypots fail to detect malicious threads injected into benign processes, and existing solutions are resource-intensive and inefficient in detecting and responding to diverse ransomware behaviors.
Innovation Solution
The use of virtual file honeypots (VFHs) that are generated on-demand, tailored to specific threat characteristics, and do not require storage or backup, allowing early detection of ransomware by monitoring system operations and applying machine learning for heuristic analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional file honeypots are used to detect malicious processes, then independent malicious processes can be detected, but malicious threads injected into benign processes cannot be identified
Solution Approach 1:
The patent creates virtual copies of real files (virtual file honeypots) that mimic the appearance and structure of legitimate system files. These virtual copies are inserted into the filesystem to attract and detect malicious threads, allowing the system to identify injected malware without disrupting normal file operations or requiring modification of actual system files.
Solution Approach 2:
The patent introduces a virtual file system layer between real files and malicious threads. This intermediary layer intercepts file access operations, presenting virtual honeypot files to malicious threads while allowing legitimate processes to access real files normally. The virtual file system acts as a mediator that enables detection without interfering with legitimate system operations.
2Reliability
If traditional honeypot files are inserted into filesystem directories to bait suspicious processes, then independent malicious processes can be identified, but system overhead and storage consumption increase
Solution Approach 1:
Instead of creating physical copies of files for honeypots, the patent uses virtual file representations that exist only in memory or as metadata. These virtual files are generated on-demand and do not require actual storage space on the filesystem, eliminating the storage overhead associated with traditional honeypot implementations.
Solution Approach 2:
The patent changes the state of honeypot files from physical storage entities to virtual representations. By transforming the fundamental parameter of file existence from tangible storage to virtual instantiation, the system achieves honeypot functionality without the associated storage consumption and backup requirements.
3Adaptability or versatility
If general honeypots are used for ransomware protection, then broad coverage is provided, but resource efficiency decreases due to system overhead
Solution Approach 1:
The patent implements localized virtual honeypots that are created only when and where needed, rather than deploying a comprehensive honeypot system across the entire filesystem. Each virtual honeypot is tailored to specific file types or directories based on the detected malicious behavior, providing targeted protection without the resource overhead of system-wide deployment.
Solution Approach 2:
The patent creates a dynamic honeypot system that adapts its behavior based on real-time analysis of malicious processes. Virtual files are generated on-demand in response to detected threats, and the system dynamically adjusts its protection strategy based on the specific characteristics of the malware, optimizing resource usage while maintaining effective coverage.
Data Source
AI summary
Systems and methods for ransomware protection in advanced injection-based attacks. Events from a driver are analyzed to identify a potentially malicious actor. A confidence level is calculated for the potentially malicious actor identification to weigh the probability that the actor is malware or a source of malware. Behavior associated with the potentially malicious actor can be collected, if it is likely that the potentially malicious actor is associated with malware, such as if the confidence level is over a predetermined threshold. Subsequently, one or more virtual honeypots are generated for the suspicious processes and the response to the virtual honeypots is included in anti-ransomware heuristic analysis.