AV Image Sensor Authentication Through Cross-Frame Validation
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Solution Overview
Problem
Autonomous vehicle (AV) sensor security and authentication are inadequately addressed, particularly when an adversary has physical access to the sensor system, leading to potential data tampering and compromised safety-critical functions.
Innovation Solution
Implementing a smart sensor system that compares image data from multiple image sensors to detect invalid data streams, generates notifications for compromised sensors, and uses adaptive impact analysis configurations to filter out non-safety related faults, ensuring the integrity of image sensor data and enhancing AV safety.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If image data from multiple sensors is compared to detect invalid data streams, then sensor security and data integrity are improved, but system complexity and processing time increase
Solution Approach 1:
The patent segments the sensor system into multiple independent image sensors (first image sensor, second image sensor) that can be individually monitored and compared. This segmentation allows the system to detect invalid data streams from specific sensors without compromising the entire system, thereby improving sensor security while managing complexity through modular comparison.
Solution Approach 2:
The patent introduces an intermediary processing mechanism that compares image data from multiple sensors and generates notifications about invalid data streams. This intermediary layer acts as a mediator between the raw sensor data and the autonomous vehicle's decision-making systems, improving data integrity while centralizing the complexity of comparison logic in a dedicated component.
2Measurement precision
If consecutive frames are analyzed to reduce false positives, then measurement precision is improved, but processing time and computational load increase
Solution Approach 1:
The patent applies preliminary action by analyzing consecutive frames in advance to establish a baseline of normal sensor behavior before making security determinations. By pre-processing and comparing multiple frames, the system reduces false positives in invalid data detection while preparing validation results ahead of time, thereby improving measurement precision without proportionally increasing processing delays during critical operations.
3Reliability
If fault detection and notification systems are implemented, then safety-critical function reliability is improved, but device complexity and energy consumption increase
Solution Approach 1:
The patent implements self-service through automatic fault detection and notification systems that monitor sensor data integrity without requiring continuous human intervention. The system autonomously compares image data, identifies invalid streams, and generates notifications, thereby improving safety-critical function reliability while minimizing energy consumption by automating monitoring tasks rather than requiring manual oversight.
Data Source
AI summary
A method includes receiving, from a sensing system of an autonomous vehicle (AV), image data including first image data and second image data. The method further includes determining, for a frame, whether an amount of image data matching between the first image data and the second image data satisfies a first threshold condition, in response to determining that the amount of image data matching satisfies a first threshold condition, identifying the frame as invalid, determining whether a number of consecutive frames determined to be invalid satisfies a second threshold condition, and in response to determining that the number of consecutive frames determined to be invalid satisfies the second threshold condition, generating a notification that the sensing system is outputting invalid data.