Hypervisor-Based Forensic Data Collection for Stateless Virtual Machines
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Solution Overview
Problem
In virtualization computing environments, ensuring compliance with regulations and standards is challenging due to the complexity and volume of data, especially with limited IT resources, and existing methods struggle with data preservation and forensic data collection from stateless virtual machines which result in data loss.
Innovation Solution
A system and method using a hypervisor to convert stateless virtual machines to persistent ones, capture digital memory, console, and CPU attribute data, and store them in immutable storage for forensic analysis, employing machine learning for data processing and artifact retention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If stateless virtual machines are used to reduce storage overhead, then storage efficiency is improved, but forensic data collection becomes impossible resulting in data loss
Solution Approach 1:
The system performs preliminary actions by converting stateless VMs to persistent VMs before forensic data collection is needed. This conversion preserves the VM state and enables subsequent forensic analysis while maintaining storage efficiency through selective persistence based on compliance risk assessment.
Solution Approach 2:
The system changes the persistence parameter of virtual machines dynamically. Stateless VMs are converted to persistent VMs when compliance requirements demand forensic data collection, and can be converted back to stateless when not needed, allowing flexible adjustment between storage efficiency and data preservation.
2Difficulty of detecting and measuring
If multiple tools are used for internal data configuration analysis, then analysis capability is improved, but operational complexity and time consumption increase
Solution Approach 1:
The system merges multiple forensic data collection tools and functions into a single integrated platform. The unified tool simultaneously performs VM state capture, memory dumping, artifact collection, and compliance assessment, eliminating the need to coordinate multiple separate tools and reducing operational complexity.
Solution Approach 2:
The forensic data collection system is designed as a universal platform that can handle multiple types of compliance requirements and data collection tasks through a single interface. It automatically adapts to different compliance standards and VM configurations without requiring separate specialized tools for each scenario.
3Adaptability or versatility
If IT resources are stretched to manage larger virtualized environments, then environment scale is improved, but compliance management capability deteriorates
Solution Approach 1:
The system implements self-service capabilities by automatically assessing compliance requirements, identifying affected VMs, and performing data collection and preservation actions without requiring extensive manual IT intervention. The automated workflows reduce the burden on stretched IT resources while maintaining compliance reliability.
Solution Approach 2:
The system performs preliminary compliance assessments and risk evaluations to identify which VMs require forensic data collection before actual compliance events occur. This advance preparation ensures that compliance requirements are met without requiring intensive resource allocation during critical compliance management periods.
Data Source
AI summary
Methods, systems, and computing platforms for data collection are disclosed. The system may include one or more hardware and virtual processors configured by machine-readable instructions. The processor(s) may be configured to electronically launch at least one virtual machine operatively connected to a virtualization layer. The processor(s) may be configured to electronically create a virtual disk for the at least one virtual machine connected to the virtualization layer so as to receive a plurality of artifact data.