LiDAR Spatial Identity Profiling for Mimicry-Resistant Authentication
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Solution Overview
Problem
Unauthorized users can mimic customer identities using spatial computing, posing a risk for unauthorized transactions and events.
Innovation Solution
Utilizing LiDAR to capture spatial image data, generate spatial computing maps, and employ machine learning to analyze these maps for anomalies, scoring the likelihood of a user's validity based on comparisons with baseline maps, and initiating appropriate actions if the score falls below a threshold.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If spatial computing is used to process events and authenticate users, then user authentication capability is improved, but vulnerability to identity mimicry attacks increases
Solution Approach 1:
The system continuously captures spatial environment data via LiDAR and compares it against stored baseline maps to provide real-time feedback on user authenticity. This closed-loop feedback mechanism detects deviations between expected and actual spatial environments, enabling dynamic authentication status updates and alerting potential identity mimicry attacks.
Solution Approach 2:
The patent introduces spatial environment maps as an intermediary verification layer between the user and the authentication system. Instead of directly trusting user claims, the system uses LiDAR-generated spatial maps of the user's environment as a mediator to indirectly verify user identity, making it difficult for attackers to mimic identities without also replicating the complete spatial environment.
2Reliability
If LiDAR spatial mapping is implemented for user validation, then authentication security is improved, but system complexity increases
Solution Approach 1:
The system leverages the LiDAR sensor's existing multi-functionality for spatial authentication purposes. The same LiDAR hardware used for general spatial computing tasks is also employed to capture authentication-relevant environmental data, eliminating the need for dedicated authentication hardware and reducing overall system complexity.
Solution Approach 2:
The patent creates simplified copies of the user's spatial environment in the form of processed maps and feature extractions. Instead of storing and comparing complete raw LiDAR point clouds, the system generates condensed spatial maps containing only the essential geometric features needed for authentication, reducing data processing complexity while maintaining security.
3Reliability
If continuous spatial environment monitoring is performed via LiDAR, then detection of unauthorized access is improved, but energy consumption increases
Solution Approach 1:
The system implements periodic spatial environment monitoring instead of continuous monitoring. LiDAR scans are performed at predetermined time intervals or when triggered by specific events, allowing the system to detect unauthorized access attempts while minimizing energy consumption by keeping the LiDAR sensor inactive between scan cycles.
Solution Approach 2:
The patent applies partial monitoring by focusing LiDAR scanning only on critical authentication zones or specific regions of interest within the user's environment. Instead of scanning the entire 360-degree environment continuously, the system directs energy-efficient partial scans toward key areas where unauthorized access is most likely to occur.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Effectively validates user identities, preventing unauthorized transactions by detecting anomalies and ensuring secure event processing.
Implementation Method 1
receive, via light detection and ranging (LiDAR) functionality of a spatial computing device, first image data of a first user environment at a first time
Data Source
AI summary
Arrangements for leveraging LiDAR for user validation are provided. A computing platform may receive, from a spatial computing device, first data of a first user environment at a first time captured via LiDAR. A first spatial computing map of the first user environment at the first time may be generated and scored to indicate a likelihood that a user of the spatial computing device is valid. The computing platform may receive a request to process an event. In response, the computing platform may cause the spatial computing device to capture, via LiDAR, second data of a current environment of the user at a current time. A second spatial computing map based on the current environment of the user at the current time may be generated and scored. The score for the second spatial computing map may be compared to a threshold to determine whether to process the requested event.