XR Visual Code Verification Against Malicious QR Content
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Solution Overview
Problem
Extended reality (XR) systems are susceptible to malicious attacks through encoded visual codes like QR codes, which can redirect users to harmful or inappropriate content, compromising user safety and interaction with the real world.
Innovation Solution
An XR system processes images to detect and decode visual codes, verifies their safety by checking for signatures and using a URL verification service, and prefetches data to identify and mitigate potential threats by indicating or blocking malicious content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If XR systems decode and process visual codes in the environment, then user interaction with encoded content is enabled, but susceptibility to malicious attacks increases
Solution Approach 1:
The system performs preliminary safety verification of visual codes by checking signatures and verifying URLs before decoding and processing them. This preliminary action prevents malicious content from being executed, resolving the contradiction by enabling safe interaction with verified encoded content while blocking malicious attacks.
Solution Approach 2:
The system introduces an intermediary verification service that acts as a mediator between the visual code and the XR system. This intermediary checks the safety of visual codes by verifying signatures and validating URLs, allowing legitimate content to pass through while blocking malicious content, thus resolving the contradiction between enabling interaction and preventing attacks.
2Reliability
If XR systems implement comprehensive visual code verification, then user safety is improved, but processing time and system complexity increase
Solution Approach 1:
The verification process is segmented into distinct components: signature verification, URL validation, and content filtering. Each component handles a specific aspect of safety verification, making the overall complex system manageable and maintainable while ensuring comprehensive user protection.
Solution Approach 2:
The system performs self-verification by checking its own visual codes against safety criteria before processing. The XR system autonomously verifies signatures and validates URLs without requiring external intervention for each code, improving user safety while managing complexity through automated self-checks.
3Object-affected harmful factors
If XR systems block malicious visual codes, then harmful content is prevented, but legitimate content may be mistakenly blocked
Solution Approach 1:
The system performs preliminary verification of visual codes by checking signatures and validating URLs before blocking any content. This preliminary action ensures that only codes failing verification criteria are blocked, preventing harmful content while minimizing false positives that would block legitimate content.
Solution Approach 2:
The verification system uses feedback from signature validation and URL verification results to make informed decisions about blocking or allowing visual codes. This feedback mechanism ensures that blocking decisions are based on actual safety concerns rather than false positives, preventing harmful content while preserving legitimate content.
Data Source
AI summary
Techniques and systems are provided for image processing. For instance, a process can include obtaining, from one or more image sensors, an image of an environment. The process can further include detecting a first visual code in the image; decoding the first visual code; verifying safety of contents of the first visual code; determining that the contents of the first visual code contain a uniform resource locator (URL); and prefetching data linked by the URL based on verifying the safety of the contents of the first visual code.