Camera Pipeline Integrity via Multi-Sensor Motion Correlation
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Solution Overview
Problem
Modern digital security is threatened by hardware attacks such as camera hijacking and hardware malfunctions, which compromise the integrity of biometric authentication systems by injecting false video feeds or malfunctioning sensor outputs.
Innovation Solution
A method and system that cross-check image frames from cameras with sensor signals from devices like IMUs to determine the correlation between motions, identifying hardware hijacks or malfunctions by comparing the degree of correlation against a threshold, thereby preventing unauthorized access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If additional hardware is deployed to detect hardware hijack or malfunction, then detection reliability is improved, but device complexity and cost increase
Solution Approach 1:
The patent makes existing camera and sensor components perform an additional security verification function. The camera captures images for both primary functionality and motion analysis, while sensors provide both operational data and integrity verification, eliminating the need for dedicated detection hardware
Solution Approach 2:
The system uses its own existing hardware components (camera and sensors) to detect potential hijacking or malfunction of those same components. The device self-verify the integrity of its hardware through cross-checking motion data from multiple sources without external assistance
2Reliability
If additional hardware is deployed to detect hardware hijack or malfunction, then detection reliability is improved, but cost increases
Solution Approach 1:
Existing camera and sensor components are made to serve dual purposes: their primary function and security verification. This eliminates the need for additional dedicated hardware, reducing manufacturing costs while maintaining detection reliability
Solution Approach 2:
The patent uses software-based processing and existing low-cost hardware components rather than expensive specialized security hardware, making the solution economically viable for widespread deployment
3Device complexity
If existing hardware components are used for cross-checking, then device complexity is reduced, but measurement precision may be affected
Solution Approach 1:
The patent introduces software-based motion analysis algorithms as intermediaries that process data from existing hardware components. These algorithms extract motion information from image frames and sensor data, enabling precise motion measurement without requiring specialized hardware
Solution Approach 2:
The system extracts motion information from the temporal dimension by analyzing changes in image frames over time, rather than relying solely on sensor measurements. This provides an additional verification dimension that maintains precision while using existing hardware
Data Source
AI summary
A method for detecting adverse conditions associated with a device includes receiving, at one or more processing devices at one or more locations, one or more image frames; receiving a set of signals representing outputs of one or more sensors of a device; estimating, based on the one or more image frames, a first set of one or more motion values; estimating, based on the set of signals, a second set of one or more motion values; determining that a degree of correlation between (i) a first motion represented by the first set of one or more motion values and (ii) a second motion represented by the second set of one or more motion values fails to satisfy a threshold condition; and in response to determining that the degree of correlation fails to satisfy the threshold condition, determining presence of an adverse condition associated with the device.