Virtual Object Shielding Using AI-Predicted Avatar Access Paths
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Solution Overview
Problem
In virtual worlds, malicious actors can interact with, damage, or misappropriate avatars and objects, and unauthorized replicas can impersonate trusted avatars, leading to security breaches and resource consumption.
Innovation Solution
A system utilizing artificial intelligence engines to determine user motives, access paths, and viewing angles in virtual worlds, generating user-specific visual content to omit unauthorized information and normalize the environment, employing real-time rendering and shielding to protect sensitive objects and avatars.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional security measures are implemented in virtual worlds, then security against malicious actors is improved, but computing resource consumption increases significantly
Solution Approach 1:
The system performs preliminary actions by predicting user motives, access paths, and viewing angles before security incidents occur. AI engines analyze user behavior patterns and pre-identify potential security threats, allowing the system to prepare protective measures in advance rather than reacting to incidents after they happen, thus reducing the computational burden during actual security events
Solution Approach 2:
The patent replaces traditional mechanical security systems (such as surveillance cameras, physical barriers, and manual monitoring) with AI-based predictive analytics. By using machine learning models to analyze behavior patterns and predict potential threats, the system substitutes resource-intensive physical and manual security measures with more efficient computational approaches that require fewer computing resources
2Measurement precision
If comprehensive monitoring of all users is implemented, then detection of malicious activities is improved, but system complexity and processing requirements increase
Solution Approach 1:
The system applies local quality by focusing monitoring resources on specific users and areas based on predicted risk levels rather than uniformly monitoring all users. AI engines identify high-risk users and locations, concentrating detection capabilities where they are most needed while reducing monitoring intensity in low-risk areas, thereby improving detection accuracy without proportionally increasing system complexity
Solution Approach 2:
The patent implements partial monitoring by selectively applying comprehensive surveillance only to users who exhibit suspicious behavior patterns or are predicted to pose security risks. Instead of monitoring all users equally, the system applies enhanced monitoring partially to high-risk individuals while using lighter monitoring for low-risk users, optimizing the balance between detection accuracy and system complexity
Data Source
AI summary
Systems, computer program products, and methods are described herein for maintaining security of virtual objects in a distributed network. Some embodiments are directed to a system including a first artificial intelligence engine configured to determine motives of users associated with avatars in a virtual world and a second artificial intelligence engine configured to determine access paths of the avatars in the virtual world. The system may include a third artificial intelligence engine configured to determine viewing angles of the avatars moving along the access paths in the virtual world and a fourth artificial intelligence engine configured to generate visual content based on attributes of the users, the motives of the users, the access paths of the avatars, and the viewing angles of the avatars moving along the access paths in the virtual world.