Vehicle Sensor Data Anonymization via Traffic Density Probability
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Solution Overview
Problem
Current anonymization methods for vehicle sensor data transmission do not effectively assess the probability of successful anonymization, as they focus on anonymization measures rather than their effects, leading to uncertainty about the environment's impact on data privacy.
Innovation Solution
A method that determines sensor data anonymization probability by calculating the likelihood of other vehicles generating the data based on traffic density and location, using statistical methods like Poisson distribution, and randomly generating anonymized time and location within predetermined intervals, ensuring that sensor data can only be transmitted if the probability meets a predetermined condition, thereby preventing unambiguous assignment to a specific vehicle.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If anonymization measures are applied to sensor data, then data privacy is improved, but the ability to assess anonymization effectiveness deteriorates
Solution Approach 1:
The patent introduces traffic density and environmental context as intermediary elements that enable assessment of anonymization effectiveness without compromising data privacy. By using these intermediaries to calculate probability values, the system can evaluate whether anonymization succeeded without revealing information about the original data source or specific vehicles.
2Loss of information
If sensor data is transmitted with precise time and location information, then data utility is improved, but the risk of identifying the source vehicle increases
Solution Approach 1:
The patent applies preliminary action by calculating the anonymization probability before data transmission occurs. The system evaluates traffic density and environmental factors in advance to determine whether anonymization conditions are met, and only transmits data when the probability indicates successful anonymization, thus preventing identification risks before they can materialize.
Solution Approach 2:
The patent changes parameters by introducing probability thresholds and traffic density metrics as dynamic criteria for data transmission. Instead of always transmitting or never transmitting, the system adjusts transmission decisions based on calculated probability values that reflect current environmental conditions, balancing data utility with anonymization security.
3Reliability
If anonymization probability calculation is performed, then anonymization effectiveness is improved, but computational complexity increases
Solution Approach 1:
The patent employs cheap short-living objects by using readily available traffic density data and environmental information that can be obtained through standard sensors and communication channels. These inexpensive, easily accessible data sources enable probability calculation without requiring complex or expensive computational resources, making the solution practical for real-world deployment.
Data Source
AI summary
The present disclosure invention relates to a method for the anonymized transmission of sensor data of a vehicle to a vehicle-external receiving unit, to an anonymizing system, and to a receiving unit, the method including the following steps: determining the sensor data at a measurement location at a measurement time, determining a traffic density in an environment of the measurement location, determining an anonymized time and/or an anonymized location, calculating an anonymization probability of the vehicle, which results from the traffic density and the anonymized time and/or location, determining whether the anonymization probability meets a predetermined anonymization condition, and if the anonymization condition is met, transmitting the sensor data to the external receiving unit, the anonymized time being indicated as a measurement time indication and/or the anonymized location being indicated as a measurement location indication.