Vehicle Sensor Image Watermarking for Spoofing Prevention
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Solution Overview
Problem
Autonomous vehicles face challenges in authenticating images from sensors to prevent spoofed data injection attacks, where unauthorized sources can upload false images, leading to compromised data integrity and potential incorrect vehicle operations.
Innovation Solution
An image watermarking system that embeds a secret, randomly generated watermark into randomly chosen pixel locations of images captured by vehicle sensors, using a cryptographic handshake to ensure each watermarked data segment carries a unique watermark, making it resistant to attacks by unauthorized sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If image watermarking is implemented to authenticate sensor images, then data integrity and security are improved, but device complexity and processing overhead increase
Solution Approach 1:
The patent applies preliminary action by embedding watermarks into sensor images before the images are processed by autonomous vehicle systems. The watermarking process prepares the data in advance with authentication information, so that verification can occur efficiently during runtime without adding significant processing burden. This resolves the contradiction by establishing security measures beforehand rather than during critical decision-making moments.
Solution Approach 2:
The patent introduces watermarks as an intermediary element between the sensor image capture and the autonomous vehicle processing system. These watermarks serve as a mediator that carries authentication information without interfering with the primary image data. The watermarking system acts as an intermediary layer that adds security functionality while maintaining compatibility with existing image processing pipelines, thus reducing the perceived complexity increase.
2Reliability
If random watermarks are embedded in sensor images, then authentication security is improved, but processing time and computational resources increase
Solution Approach 1:
The patent applies local quality by embedding watermarks in specific, strategically chosen locations within sensor images rather than uniformly across the entire image. The system identifies and modifies only the necessary pixels or regions that contain sufficient information for authentication. This selective approach maintains high authentication security while minimizing the computational overhead and processing time required for watermark embedding and verification.
3Reliability
If watermark validation is performed on all incoming images, then data authenticity is improved, but system productivity and operational speed decrease
Solution Approach 1:
The patent applies partial action by performing watermark validation selectively rather than on every single incoming image. The system validates watermarks based on risk assessment, image type, source reliability, and other contextual factors. For low-risk images from trusted sensors, validation may be skipped or performed with reduced scrutiny. This approach maintains high data authenticity for critical images while preserving operational speed for routine operations, thus resolving the contradiction between thorough validation and productivity.
Data Source
AI summary
A computer includes a processor and a memory, the memory storing instructions executable by the processor to collect a digital image that includes a plurality of pixels with a first sensor, input a reference data string, a key data string, and a set of collected data from a second sensor into a permutation generator that outputs a watermark data string, and embed the watermark data string in the digital image at specified pixels in the plurality of pixels.