Digital Resource Tracking in Virtual Reality Environments
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Solution Overview
Problem
There is a need to detect and protect against wrongful activities associated with resource exchange events conducted in virtual computing environments, such as the Metaverse, where digital resources are exchanged for physical goods and services.
Innovation Solution
The system tracks digital resources used in resource exchange events by tagging them with data identifying the location within virtual reality computing environments. Machine-learning algorithms analyze these tags to determine movement patterns of digital resources across multiple virtual environments, identifying connected parties and suspicious activities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If digital resources are tracked and tagged across multiple virtual reality computing environments, then security and detection of wrongful activities are improved, but device complexity and data processing requirements increase
Solution Approach 1:
The system segments the tracking of digital resources by implementing location tags that identify specific virtual reality computing environments and sub-environments. This segmentation allows the system to track resources across multiple environments without treating them as a single complex system, enabling modular analysis of resource movement patterns in each environment while maintaining overall security across the distributed system.
2Measurement precision
If machine-learning algorithms analyze tags to determine resource exchange event movement patterns, then detection precision of suspicious activities is improved, but use of energy and computational resources increase
Solution Approach 1:
The system applies machine-learning algorithms selectively to analyze tags and determine movement patterns only when resource exchange events occur across multiple virtual reality computing environments. Rather than continuously analyzing all data, the system performs partial analysis focused on specific patterns of resource movement that indicate potential wrongful activities, reducing overall computational energy while maintaining high detection precision for suspicious activities.
3Reliability
If signals are generated to prevent subsequent resource exchange events involving suspicious parties, then protection against wrongful activities is improved, but ease of operation and system accessibility decrease
Solution Approach 1:
The system introduces signals as intermediary mechanisms that mediate between the detection of suspicious activities and the prevention of subsequent resource exchange events. These signals act as a layer of protection that can be selectively applied to specific parties or resources without completely blocking system accessibility. The intermediary signals enable targeted protection while maintaining ease of operation for legitimate users and activities.
Data Source
AI summary
Tracking digital resources used in resource exchange events conducted in virtual reality computing environments. Digital resources used in resource exchange events conducted in virtual reality computing environments are tagged with data that at least identifies the location of the resource exchange event in terms of virtual reality computing environment and/or sub-environments. In response, machine-learning algorithm(s) are implemented that analyze the tags to determine resource exchange event movement patterns for specific digital resources. The resource exchange event movement patterns may include digital resource movement across multiple different virtual computing environments.