Vehicle Security Anomaly Detection via Sensor Data Correlation
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Solution Overview
Problem
Current vehicle security systems face challenges in effectively detecting anomalies and preventing attacks on in-vehicle networks, particularly due to the constant evolution of hacking techniques that exploit existing security mechanisms like message encryption and intrusion detection systems, without adding additional physical sensors.
Innovation Solution
A vehicle security enhancement system utilizes the data consistency from existing sensors such as Camera, RADAR, LiDAR, and SONAR to implement a robust anomaly detection mechanism, analyzing multiple sensor data to identify potential attacks without adding physical sensors, thereby providing a simple and low-complexity solution to detect CAN message payload manipulation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If additional physical sensors are added to enhance anomaly detection capability, then detection reliability is improved, but device complexity increases
Solution Approach 1:
The patent applies multi-functionality by enabling existing sensors (camera, radar, LiDAR, sonar) to serve dual purposes: their original sensing functions plus anomaly detection functions. By analyzing the consistency of data from these multi-functional sensors, the system achieves improved detection reliability without adding dedicated physical sensors, thereby avoiding increased device complexity.
Solution Approach 2:
The system employs self-service by utilizing the data from existing sensors to detect anomalies within the same system. The sensors serve themselves by providing reference data that enables the anomaly detection mechanism to identify inconsistencies caused by attacks, eliminating the need for separate detection hardware and reducing overall system complexity.
2Reliability
If complex security mechanisms are deployed to protect in-vehicle networks, then security reliability is improved, but ease of operation deteriorates
Solution Approach 1:
The patent implements feedback by continuously monitoring the consistency between reference sensor data and CAN bus message data. When inconsistencies are detected, the system automatically triggers anomaly detection and security responses. This feedback mechanism provides robust security reliability while maintaining operational simplicity through automated detection and response processes that do not require complex manual intervention.
3Reliability
If existing security mechanisms like message encryption and intrusion detection are used, then basic security is provided, but adaptability to new hacking techniques deteriorates
Solution Approach 1:
The patent applies dynamics by implementing a flexible anomaly detection mechanism that adapts to various attack types without requiring predefined attack signatures. The system dynamically analyzes sensor data consistency to detect novel hacking techniques, combining the stability of existing security mechanisms with the adaptability needed to counter evolving threats. This dynamic approach maintains basic security reliability while enhancing versatility against new attack vectors.
Data Source
AI summary
This disclosure describes systems, methods, and devices related to vehicle security enhancement. For example, a vehicle may receive a plurality of data values from an onboard diagnostic system (OBD) of a vehicle, wherein a first data value is received from a first sensor of the vehicle and a second data value is received from a second sensor of the vehicle. The vehicle may determine a third data value received from a controller area network (CAN) bus of the vehicle. The vehicle may determine the third data value is associated with a false message originating from a device external to the vehicle based on performing a correlation analysis between the first value, the second value and the third value. The vehicle may discard the third data value based on the correlation analysis.