Location privacy protection method for social vehicle networking based on double k-anonymity

Abstract

The invention discloses a method for protecting the location privacy of social vehicle networking based on double k-anonymity. First, a cloud server is set up as a trusted third party, vehicle users are constructed as user groups, and user IDs, locations and service requests are collected, The location and the request set are randomly scrambled and recombined to construct a user data matrix, and then use the random matrix to encrypt the user data matrix. After the cloud server uses the encrypted user data to request related services from the service provider, after receiving the feedback After the location service information is located to the user ID, the service content is fed back to the corresponding user. The present invention uses the method of randomly scrambled user data and random matrix encryption to perform double k-anonymity on both user location and service request content, so as to reduce the correlation between user ID, location and service request and users, thereby reducing the accuracy of attackers. The probability of identifying the user can protect the privacy of the user's location.

Description

technical field [0001] The invention belongs to the technical field of Internet of Vehicles, and more particularly, relates to a method for protecting the location privacy of social Internet of Vehicles based on double k-anonymity. Background technique [0002] With the continuous development of science and technology, ordinary social networks can no longer meet the daily needs of users. In order to ensure the convenience and safety of the user's driving process, a network paradigm that combines the two types of Internet of Vehicles and social networks - the Social Internet of Vehicles came into being, and the intelligent networked car has become the carrier of the next mobile social network. After the car, the mobile phone social function is abandoned, and the communication device of the vehicle itself is used to complete the social interaction. Social Internet of Vehicles is a subset of the Internet of Vehicles. It uses intelligent connected vehicles in motion as nodes, a...

AI Technical Summary

Problems solved by technology

[0005] The existing location privacy protection methods based on user behavior information have high computational complexity and overhead, and may affect the quality of services enjoyed by users. Therefore, the location privacy protection effect of such methods is not ideal

In addition, although the location privacy protection technology based on the user relationship network can guarantee the quality of service obtained by the user, the degree of protection of the user's location privacy is limited.

The last is the location privacy protection method based on user attribute information. By changing the user ID to achieve the purpose of protecting location privacy, compared with the above two types of methods, it does not affect the service quality required by the user and does not require complicated calculations. The user's location privacy protection is limited

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