Abstract
With the growth of big data and open data in recent years, the importance of data anonymization is increasing. Original data need to be anonymized to prevent personal identification from being revealed before being released to the public. There is a growing variety of de-identification methods which have been proposed to reduce the privacy issues, however, there is still much to be improved. The purpose of this study is to demonstrate the possibilities of re-identification from masked data, and to compare the pros and cons of different de-identification methods. A set of electronic toll collection data from Taiwan was used and we successfully re-identified vehicles with specific patterns. Four de-identification methods were performed and finally we compared the strengths and weaknesses of these methods and evaluated their appropriateness.
Highlights
Cyber-physical road systems have made considerable progress through the development of technologies such as vehicle communications, internet of vehicles (IoVs), and smart transportation.For example, the IntelliDrive system in United States allows cars on the road to communicate over short distances in real-time through roadside facilities
This accounts for 67.79% of the total number of trips, making small passenger cars the most common type of vehicle traveling on the national highways
Buses made 386,604 trips, or 1.51% of the total number of trips, making them the least numerous of the vehicles traveling on the national highways
Summary
Cyber-physical road systems have made considerable progress through the development of technologies such as vehicle communications, internet of vehicles (IoVs), and smart transportation.For example, the IntelliDrive system in United States allows cars on the road to communicate over short distances in real-time through roadside facilities. The installation of GPS in specific vehicles (e.g., buses for public transport) allows for the collection of information related to their driving dynamics, these systems have been installed by transportation enterprises and the data is only used internally. We obtained the following information by analyzing the raw data by vehicle type: in the data interval from 16/10/2015 to 23/10/2015, 25,561,407 trips were made over eight days, where 17,372,861 of these trips were made by small passenger cars. This accounts for 67.79% of the total number of trips, making small passenger cars the most common type of vehicle traveling on the national highways. The data was compartmentalized into the first four days and last four days, which were used as training and testing/validation datasets, respectively
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