With the rapid development of location technologies, such as GPS, Wi-Fi and Radio Frequency Identification (RFID), Location-Based Service(LBS) are becoming increasingly popular in people's lives. While enjoying the great convenience brought by LBS to life, users' privacy is exposed to the risk of leakage. The contemporary traditional LBS privacy protection mainly considers spatio-temporal information but ignores inferring attacks based on user-related background information which leads to the attacker can use the user's background information to mine the user's identity information, personal preferences, behavioral habits, and other privacy information. According to the user's real trajectory influenced by the key map points in the area, this paper proposes an LBS privacy protection scheme incorporating map semantic information. The method combines the user's location trajectory and map influence to construct a privacy protection model with synergistic time, space, and map influence. And according to the model, the secure anonymization area that matches the user's motion logic and the semantic match between the user's corresponding map point is screened out, thus finally achieving the role of protecting the user's LBS privacy information.