Ransomware Detection Metrics for Cloud Workload Reallocation
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Solution Overview
Problem
Cloud computing systems are vulnerable to ransomware attacks that can encrypt client data and become gateways for further damage, often bypassing standard anti-virus protections and targeting hardware, with laptops and servers being particularly prone.
Innovation Solution
A detection mechanism distinguishes between transient and sustained encryption/decryption events, monitoring kernel-level encryption/decryption instructions and security states to identify ransomware attacks, and upon detection, migrates workloads to unaffected instances using a repaving system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If standard anti-virus protections are used, then basic security is provided, but ransomware attacks can bypass them and encrypt client data
Solution Approach 1:
The patent introduces an intermediary detection mechanism that sits between the standard anti-virus protections and the ransomware threat. This mechanism uses hardware performance counters and exception-level transition monitoring to detect encryption activities before they can complete, acting as an additional layer that intercepts and identifies malicious behavior that standard protections miss.
Solution Approach 2:
The patent replaces traditional software-based anti-virus scanning with a hardware-level detection system using performance counters and exception monitoring. This substitution occurs at the processor level, where hardware counters track encryption-related operations and exception transitions detect suspicious state changes, providing detection capabilities that operate independently of software anti-virus solutions.
2Reliability
If workloads are migrated to unaffected instances upon ransomware detection, then system integrity is maintained, but cloud infrastructure complexity increases
Solution Approach 1:
The patent implements preliminary action by pre-configuring the detection mechanism and response protocols before ransomware attacks occur. The system pre-estimates the likelihood of attacks using baseline metrics and has predetermined response actions ready to execute, allowing rapid workload migration without requiring complex real-time decision-making infrastructure.
Solution Approach 2:
The patent establishes a feedback loop where detection metrics continuously monitor system state and feed into the workload management system. When encryption likelihood exceeds thresholds, the feedback triggers automated workload migration decisions, creating a closed-loop system that adapts to threats while maintaining manageable infrastructure complexity through rule-based responses.
Data Source
AI summary
Aspects of the disclosure include a dynamic cloud workload reallocation based on an active ransomware attack. An example method includes receiving a first message that a computing instance is potentially infected by ransomware. The method further includes receiving a security state-based metric related to the computing instance based at least in part on the first message. The method further includes comparing the security state-based metric to a threshold metric. The method further incudes determining a likelihood of a ransomware attack based at least in part on the comparison. The method further includes transmitting second message to a job scheduler to reschedule workloads directed toward the computing instance based at least in part on the determination.