Location anonymization-based privacy protection method and apparatus

Abstract

The invention provides a location anonymization-based privacy protection method. The method comprises the steps of 1) determining an anonymity degree k according to a currently queried privacy level, wherein the higher the privacy level is and the higher the anonymity degree k is; 2) creating a plurality of candidate anonymity sets with k elements by taking the anonymity degree k as the size of a currently queried anonymity set; 3) searching for one candidate anonymity set with a maximum query probability set entropy from the created candidate anonymity sets to serve as the anonymity set; 4) generating an upper bound and a lower bound of an anonymity distance according to the privacy level, wherein the higher the privacy level is, the larger the upper bound of the anonymity distance is, and the larger the lower bound of the anonymity distance is; and 5) generating an anonymous location used for replacing a currently queried real location according to the generated upper bound and lower bound of the anonymity distance in the range of the anonymity set. The invention furthermore provides a corresponding privacy protection apparatus. According to the method and the apparatus, the LBS (Location Based Service) quality is improved while the location privacy protection is realized, and different demands of different users on privacy protection can be guaranteed.

Description

technical field

[0001] The invention relates to the technical field of computer data mining and analysis, in particular, the invention relates to a privacy protection method and device based on location anonymity. Background technique

[0002] Currently, Location Based Service (Location Based Service, LBS for short) has been widely used in the mobile Internet. The LBS acquires Point of Interest (POI for short) information through the location information of the user, and then provides services in various fields for the user based on the POI. However, while LBS brings convenience to users, it also threatens users' personal privacy. For example, attackers can derive personal sensitive information such as home addresses, living habits, or health conditions based on users' location information. In other words, the leakage of location information poses a serious threat to personal privacy, so the research on privacy protection based on location services has positive significance...

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