Ransomware Detection via Data Block Change Rate Analysis
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Solution Overview
Problem
Current methods for detecting ransomware attacks are costly, time-consuming, and often only employed during infrequent backups, leading to potential exposure of backup data and delayed detection, which can result in significant damage before the attack is mitigated.
Innovation Solution
Implementing a system that enables changed block tracking, takes snapshots of data blocks at multiple times, and determines the rate of change and pattern of changes to detect anomalies exceeding thresholds, triggering scans for ransomware when unusual activity is detected.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If traditional ransomware detection methods are used, then detection accuracy may be adequate, but detection time is delayed and damage occurs before mitigation
Solution Approach 1:
The system performs preliminary monitoring of data block changes and identifies suspicious patterns before ransomware completes its encryption process. By detecting anomalies in data modification patterns early in the attack lifecycle, the system enables mitigation before significant damage occurs, resolving the contradiction between early detection and reliable identification.
Solution Approach 2:
The patent segments the detection process into multiple stages: continuous monitoring of data block changes, analysis of change patterns, identification of suspicious behaviors, and final ransomware confirmation. This segmentation allows the system to reduce detection time through continuous monitoring while maintaining reliability through progressive verification at each stage.
2Loss of time
If continuous monitoring and scanning is performed, then early detection capability is improved, but system cost and complexity increase
Solution Approach 1:
The system applies partial monitoring by focusing only on data blocks that exhibit suspicious change patterns rather than continuously scanning all data. By monitoring all data blocks for changes but only performing full analysis on those showing anomalous patterns, the system achieves early detection without the prohibitive cost and complexity of continuous comprehensive scanning.
3Use of energy by moving object
If infrequent backups are used for detection, then system resource consumption is reduced, but detection is delayed and backup data becomes exposed
Solution Approach 1:
The system maintains continuous monitoring of data block changes without requiring periodic backup operations. This continuous observation enables real-time detection of ransomware activity while consuming minimal resources, as the system only processes change metadata rather than copying entire datasets. The continuous action resolves the contradiction by enabling timely detection without the energy cost of frequent backups.
Data Source
AI summary
In general, one or more embodiments of the invention relates to systems and methods for detecting ransomware attacks earlier and closer to the time of attack. The ransomware attack can be detect by determining a change rate of data blocks between snapshots. The ransomware attack can also be detected by determining the pattern of changes in the blocks deviates from a normal pattern. By making these determinations, a quick identification of possible ransomware attacks can be made and other methods of mitigating the attack can be deployed when they are may still be useful to mitigate potential damage to a user's data.