A Personalized Location Privacy Protection Method Based on Differential Privacy

Abstract

The invention belongs to the field of information security, and relates to a personalized location privacy protection method based on differential privacy; the method includes setting the current sensitive location point and target interest point by the vehicle user; and calculating the radius of the sensitive circle by using a plane Laplace noise mechanism; Establish a multi-attribute route selection benefit decision matrix; use the weight distribution algorithm of information entropy theory to establish a multi-attribute route selection benefit function; calculate the benefit value of each driving route, and use the sorting algorithm to select the route with the highest benefit as the driving route; The service location points outside the sensitive circle are allocated privacy budgets according to the sensitive distance ratio, and the remaining privacy budget is allocated to the service location points in the sensitive circle; within the false generation range, the planar Laplacian mechanism is used according to the privacy budget of the service location points Generate a false location; the invention comprehensively considers the utility and privacy of the user's choice of driving route, realizes the quantification of the user's route selection benefit function in the vehicle network, and provides personalized privacy services.

Description

Technical field [0001] The invention belongs to the field of information security, in particular to the field of vehicle network information security, specifically a personalized location privacy protection method based on differential privacy. Background technique [0002] With the development of the in-vehicle network, the location-based service (LBS) provides users with more diverse services, and has brought many conveniences for users. For example, people can get information on the hotel and hospital by continuously submitting its location information to the service provider. However, this frequent query may lead to serious privacy leaks, and attackers can invade service providers to speculate on user sensitive information. Therefore, when the user enjoys the service provided by the LBS, location privacy is a problem that needs to be solved. [0003] In response to the privacy problem of LBS in the above-mentioned vehicle network, researchers have already launched a large num...

AI Technical Summary

Problems solved by technology

However, Option 1 does not consider the individual privacy needs of users, which may result in excessive privacy protection in some places, and insufficient privacy protection in some places.

The second option does not meet the user's personalized attribute requirements, and cannot provide users with personalized privacy protection measures.

[0009] All in all, traditional differential privacy protection technology cannot provide personalized privacy protection for vehicle users

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