Autonomous Vehicle Sensor Voting Against Spoofed Perception
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Solution Overview
Problem
Autonomous vehicles face security risks due to incorrect sensor inputs from misperception or intentional spoofing, which can lead to catastrophic errors in control systems, as existing control systems are insecure and vulnerable to external attacks.
Innovation Solution
An autonomous vehicle system that emits and senses multiple modalities of electromagnetic sensor signals, such as different polarizations or frequencies, and uses majority voting between these modalities to generate control inputs, providing end-to-end self-controlled security and enhancing reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional sensor systems are used in autonomous vehicles, then the system complexity is low and ease of manufacture is good, but the security and reliability are poor due to vulnerability to spoofing and misperception
Solution Approach 1:
The patent segments the sensor system into multiple independent sensor types (e.g., LIDAR, radar, cameras) that operate in parallel. Each sensor modality processes environmental data independently, and their outputs are fused to make control decisions. This segmentation allows the system to achieve higher reliability through diversity while managing complexity through modular architecture.
Solution Approach 2:
The patent introduces a new dimension of security by using multiple sensor modalities that operate in different spectral domains (optical, radio frequency, etc.). This dimensional diversity makes it difficult for attackers to spoof all modalities simultaneously, as each modality requires different attack mechanisms. The system compares intermediate outputs across these dimensions to detect anomalies.
2Reliability
If multiple modalities of sensor signals are used, then the security against spoofing is improved, but the device complexity and manufacturing difficulty increase
Solution Approach 1:
The patent employs a universal processing architecture that handles multiple sensor modalities through a common framework. The same processing circuits and algorithms are used across different sensor types, allowing the system to benefit from economies of scale in manufacturing. This multi-functionality approach reduces the need for separate dedicated processing units for each sensor type, thereby easing manufacturing complexity.
Solution Approach 2:
The system performs self-verification by comparing intermediate outputs from different sensor modalities. Each sensor modality serves as a check on the others, with the system automatically detecting inconsistencies that may indicate spoofing. This self-service mechanism reduces the need for external security validation systems, simplifying the overall manufacturing process.
3Reliability
If multiple modalities of sensor signals are processed with majority voting, then the reliability and security are improved, but the processing time and loss of time increase
Solution Approach 1:
The patent performs preliminary processing of sensor data to generate intermediate outputs before the final decision-making stage. By pre-processing data from multiple modalities and preparing intermediate results in advance, the system reduces the computational burden during critical decision moments. This preliminary action allows for thorough comparison and majority voting without excessive delay in the control loop.
Solution Approach 2:
The system implements a staged processing approach where not all sensor modalities are fully processed in every situation. The system performs partial processing based on the current operational context, only invoking full multi-modality comparison when security concerns arise or when sensor data inconsistencies are detected. This selective approach maintains high reliability while minimizing unnecessary processing time.
Data Source
AI summary
Techniques are presented to improve the security of operation for autonomously driving automobiles and other transportation or robotic equipment with varying degrees of autonomous operation. This can include an end-to-end closed-system support of control sensors' own signal emission and self-controlled frequency or polarization, which can be hard to decipher by external attackers. The control systems can employ majority voting by multiple perception results from both time (e.g., samples from same polarization in time series of an epoch, given the fact of oversampling) and space (e.g., different polarizations or sensor types) domains for enhanced security.