## 1 Introduction  
With the rapid development of smart terminal technology, positioning technology, and mobile Internet technology, location-based service (LBS) is increasingly penetrating all aspects of life, such as inquiring about nearby restaurants, hotels, and so on, bringing great convenience to people. In reality, people enjoy location-based services over the cyber. Considering the network security situation, people inevitably suffer serious cyber risks, e.g., malware [1], spyware [2], encryption for malicious purposes [3], and zero-day attacks [4]. Privacy leakage, as one of the cyber risks, is drawing more and more attention. At present, the intrinsic privacy leakage for LBS is increasingly becoming a huge challenge for protecting a user's privacy. In applying LBS, a user submits a request, which contains locations and query content, to the LBS server. However, users' locations and query content are often leaked, due to the compromise between the provider (LP) and attackers. As a result, users are exposed to privacy leakage when using an LBS. For example, attackers can infer a user's privacy (e.g., where the user works and goes for a dinner, where the user stays overnight) from locations and query content (e.g., \"which hospitals are nearby\"). Even then, users still need to use LBSs in many cases. Thus a location privacy-preserving technology must settle these problems to protect locations and so query content is not disclosed. In this work, we investigate how to protect users' privacy in the scenario of a continuous query. In this scenario, to protect users' privacy, researchers have presented a variety of methods like privacy policy [5; 6], distortion, encryption [7; 8; 9; 10; 11], and so on. Among these methods, distortion techniques, such as pseudonym, obfuscation, and dummy, are most widely used to protect privacy. Pseudonym techniques [12; 13] protect users' privacy by replacing or directly deleting users' identity identifiers with a false or temporary pseudonym. While users can use pseudonyms for privacy protection, adversaries can still infer the user's real identity by analyzing the spatial-temporal correlation of continuous queries [13]. Obfuscation techniques [14; 15; 16] protect the users' privacy by generalizing or perturbing the time and locations in LBS queries, and then the users' precise locations are not recognized. However, submitting inaccurate locations will reduce the quality of the service. An effective approach is to maintain the quality of service while ensuring that users' privacy is not leaked. Considering that the dummy techniques [13; 17; 18; 19; 20; 21; 22; 23; 24; 25; 26; 27] to protect the privacy of a user are to add dummy queries to the real query and do not reduce the quality of the service. They are feasible in our work. In this paper, we focus on how to hide a user's locations or query content among dummies in the scenario of a continuous query. While existing dummy techniques solved the privacy leakage in the LBS query, they mainly focus on the scenario neighbor query in which a user sends queries in different locations and they neglect the scenario where the same user sends a short-time continuous query in the same location (called'scenario of this paper' for simplicity ). Figure 1 shows an example of privacy leakage in the scenario of this paper. In the example, the real user sends three queries in location \(L\) to query nearby points of interest (POI). For each query, three dummy users are selected to form an anonymous group. However, existing techniques, e.g., the distortion technique, only select one of the three queries (we assume the first query is selected) to hide the location and query content since existing techniques neglect the scenario of this paper. So, we assume not one of the users sends three queries except the real user \(u_{1}\) in the example. For four query content sent by all users in each query, we assume the first query has three query categories, while there is only one query category for the second and third query, respectively.