Autonomous Vehicle Sensor Data Security via Cryptographic Validation
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Solution Overview
Problem
Autonomous vehicles face vulnerabilities in data security, particularly with sensors being exploited by hackers, leading to potential system failures and safety risks due to the sharing of data across distributed networks.
Innovation Solution
Implementing inter-process communication security via key management, which includes digitally signing sensor data, generating and encrypting session keys, and using message authentication codes to validate data integrity and authenticity, along with anonymizing identification data and employing machine learning for obfuscation and validation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If sensor data is shared across distributed networks for autonomous navigation, then navigation capability and data utility are improved, but security vulnerabilities and risk of malicious tampering increase
Solution Approach 1:
The patent applies preliminary action by digitally signing sensor data at the source before transmission across distributed networks. This pre-authentication ensures that data integrity is verified before it enters the network, preventing malicious tampering while enabling safe data sharing for autonomous navigation.
Solution Approach 2:
The patent introduces cryptographic intermediaries (digital signatures, session keys, and message authentication codes) that mediate between the sensor data and the distributed network. These intermediaries verify data authenticity without requiring direct trust between network participants, enabling secure data sharing.
2Reliability
If digital signatures and cryptographic validation are implemented for all sensor data, then data security and authenticity are improved, but processing time and computational complexity increase
Solution Approach 1:
The patent performs digital signing of sensor data at the source before transmission, so validation occurs during data reception rather than during critical processing phases. This preliminary authentication minimizes processing time delays during autonomous navigation operations.
Solution Approach 2:
The patent implements selective cryptographic validation, applying full digital signature verification only to critical sensor data while using lighter-weight message authentication codes for routine data. This partial application of security measures balances reliability with processing efficiency.
3Reliability
If session keys are generated and encrypted for each sensor communication, then data confidentiality is improved, but key management complexity and system overhead increase
Solution Approach 1:
The patent generates and distributes encrypted session keys to sensors before data transmission begins. This preliminary key distribution establishes secure communication channels in advance, simplifying ongoing key management during autonomous navigation operations.
Solution Approach 2:
The system implements automated session key generation and distribution, where the central processor automatically manages key creation, encryption, and delivery to sensors without requiring manual intervention. This self-service approach reduces key management complexity despite the overhead of individualized key handling.
4Reliability
If identification data is anonymized through obfuscation and machine learning, then privacy security is improved, but data processing complexity and computational requirements increase
Solution Approach 1:
The patent replaces traditional mechanical anonymization methods with machine learning-based obfuscation techniques. The machine learning model dynamically transforms identification data in ways that preserve privacy while maintaining data utility for navigation, reducing the need for complex rule-based processing systems.
Solution Approach 2:
The patent changes the parameters of identification data through machine learning-driven transformations, converting sensitive information into obfuscated representations that maintain statistical properties needed for navigation while eliminating personally identifiable information. This parameter transformation approach balances privacy security with processing efficiency.
Data Source
AI summary
Among other things, we describe systems and method for implementing data security in an autonomous vehicle system. The systems and methods can include inter-process communication security via key management, in which asymmetric cryptography and other validation techniques are used to validate data received from sensors. The systems and method can also include penetrative testing, in which valid sensor inputs are modified and transmitted throughout a distributed network through one or more sensors.