Endpoint Ransomware Mitigation via Honeypot File Detection
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Solution Overview
Problem
Current anti-virus, anti-spyware, and anti-malware software are ineffective in mitigating the effects of ransomware infections, which restrict access to computer systems by encrypting files or locking them, often propagating as Trojan payloads disguised as legitimate files.
Innovation Solution
A method and system that detects access events to hidden data items on an endpoint, modifies file properties to prioritize honeypot files, and takes actions such as slowing down or preventing processes from accessing these files, while analyzing heuristic signatures to determine if the process is ransomware, thereby creating backups and preventing data deletion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional anti-virus and anti-malware software is used to protect against ransomware, then general malware protection is provided, but ransomware attacks cannot be mitigated because these programs fail to detect or prevent ransomware encryption of files
Solution Approach 1:
The system deploys honeypot files in advance across the file system before a ransomware attack occurs. These decoy files are positioned to be accessed first by ransomware processes, allowing the system to detect and respond to attacks before real user files are encrypted. This preliminary deployment of protective measures enables early detection and intervention.
Solution Approach 2:
The honeypot files serve as an intermediary between the ransomware process and the actual user files. Instead of directly protecting user files, the system uses these decoy files as a buffer to detect ransomware behavior first, allowing time for protective actions to be taken against the ransomware process before it reaches real files.
2Measurement precision
If honeypot files are deployed to detect ransomware processes, then ransomware detection capability is improved, but false positives may occur from legitimate processes accessing these hidden files
Solution Approach 1:
The system dynamically adjusts its response based on the behavior patterns observed. When a process accesses honeypot files, the system monitors subsequent actions to determine if the process exhibits ransomware-like behavior patterns. This dynamic analysis allows the system to differentiate between legitimate processes that may accidentally access hidden files and actual ransomware attacks.
Solution Approach 2:
The system implements feedback mechanisms by monitoring process behavior after initial honeypot file access. It analyzes whether the accessing process continues to access multiple honeypot files or attempts to encrypt them, using this feedback to confirm ransomware detection or dismiss false positives. This multi-stage verification reduces false positive rates.
3Productivity
If protective actions are taken against processes accessing honeypot files, then ransomware processes are slowed or prevented, but legitimate processes may be interrupted
Solution Approach 1:
The protective actions applied to processes are dynamic and adaptive. The system monitors process behavior patterns and adjusts the intensity of protective measures accordingly. For processes showing clear ransomware behavior, strong protective actions are taken. For processes with ambiguous behavior, the system applies lighter monitoring or allows continued execution, thereby minimizing impact on legitimate processes.
Solution Approach 2:
The system applies protective actions selectively rather than universally. When a process accesses honeypot files, the system applies protective measures to that specific process rather than blocking all file access system-wide. This partial action approach ensures that only potentially malicious processes are affected while legitimate processes continue to function normally.
4Measurement precision
If file access monitoring is implemented to detect ransomware, then detection capability is improved, but system performance may degrade due to continuous monitoring overhead
Solution Approach 1:
The system implements monitoring with local quality by focusing surveillance resources on specific high-risk areas of the file system where honeypot files are deployed. Instead of monitoring all file access system-wide, the system concentrates monitoring efforts on directories and file types most vulnerable to ransomware attacks, thereby reducing overall system overhead while maintaining effective detection capability.
Solution Approach 2:
The system performs preliminary actions by pre-positioning honeypot files in strategic locations before attacks occur. This allows the system to passively detect attacks when ransomware processes attempt to access these pre-placed files, rather than requiring active continuous monitoring of all file access. The preliminary deployment creates automatic detection triggers that consume minimal system resources.
Data Source
AI summary
Computerized methods and systems mitigate the effect of a ransomware attack on an endpoint by detecting access events associated with requests by processes, including ransomware processes, to access data items on the endpoint. The data items are hidden from the operating system processes executed on the endpoint. In response to detecting an access event, an action is taken against the process associated with the access event.