Vehicle UWB STS Verification for Fake Leading Edge Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing UWB communication systems are vulnerable to attacks that manipulate time of arrival measurements, allowing unauthorized access to vehicles by injecting fake leading edges, compromising security and distance measurement accuracy.
Innovation Solution
Implementing a vehicle control device with a digital signal processor (DSP) that divides received STS fields into sub-fields, performs cross-correlation calculations, and verifies the consistency of time of arrival measurements to detect and invalidate abnormal signals, ensuring only legitimate signals unlock vehicle functions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If cross-correlation-based STS verification is used, then distance measurement function is achieved, but security vulnerability occurs allowing fake leading edge generation
Solution Approach 1:
The patent divides the 4096-bit STS field into multiple sub-fields (e.g., 8 sub-fields of 512 bits each) and performs separate cross-correlation calculations on each sub-field. This segmentation allows the system to verify consistency across multiple independent measurements, preventing attackers from successfully polluting the entire CIR output with a single injected signal.
Solution Approach 2:
The patent implements a feedback mechanism where the system checks whether the leading edges identified from different sub-fields are consistent with each other. If the leading edges from multiple sub-fields do not align within an expected tolerance range, the system rejects the measurement and requests re-transmission, thereby preventing fake leading edge acceptance.
2Reliability
If detailed STS verification is performed, then security is enhanced, but distance measurement performance deteriorates
Solution Approach 1:
The patent performs cross-correlation on multiple sub-fields (excessive action) but only accepts the measurement if the leading edges from these sub-fields are consistent. This partial acceptance approach ensures security through thorough verification while maintaining measurement precision by rejecting inconsistent results that would indicate attacks or errors.
3Object-affected harmful factors
If attacker injects strong signal into STS field, then distance shortening attack succeeds, but signal intensity adjustment is required for each field
Solution Approach 1:
By segmenting the STS field into multiple sub-fields and requiring consistent leading edge identification across all segments, the system prevents distance shortening attacks without requiring complex per-field signal intensity adjustment. The segmentation itself creates the complexity barrier for attackers while maintaining relatively simple receiver processing.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances vehicle security by preventing unauthorized access and maintaining accurate distance measurements through simple software modifications, thereby reinforcing the STS verification scheme.
Implementation Method 1
perform cross-correlation calculation of the divided sub-fields and sub-templates previously stored in the storage, extract times of arrival of the vehicle control signal from the results of performing the cross-correlation calculation
Data Source
AI summary
A vehicle is configured to provide a security function using an electronic key. A method includes receiving a vehicle control signal through an antenna device of the vehicle, extracting a scrambled timestamp sequence (STS) field in the vehicle control signal, dividing the extracted STS field into sub-fields, each of which has a predefined certain length, performing cross-correlation calculation of the divided sub-fields and sub-templates previously stored in storage of the vehicle, extracting times of arrival of the vehicle control signal from the results of performing the cross-correlation calculation, and determining the vehicle control signal as a normal signal when consistency of distribution locations of the times of arrival in the results of performing the cross-correlation calculation is greater than or equal to a predefined reference value and determining the vehicle control signal as an abnormal signal when the consistency is less than the predefined reference value.


