# Secure Indoor Localization Based on Extracting Trusted Fingerprint
WiFi based on indoor location systems typically uses WiFi access points (APs) to calculate the user's possible locations [13]. In the indoor environment, the extensive application of WiFi makes WiFi-based IPS possible in many places. The localization method based on RSSI [14] has become the mainstream method of indoor localization, with the advantages of low cost, wide coverage and no need for any other hardware [15]. The method is generally divided into two categories. The trilateration algorithm is based on the principle of distance crossover; the fingerprint location method is based on the database and the specific geometric or probabilistic algorithm to calculate the location of unknown points [16]. The extraction of RSSI is crucial for trilateration algorithms and fingerprinting methods [17]. The refinement of RSSI directly affects the accuracy of positioning; [PERSON]; et al. [18] consider that different handsets can have an impact on RSSI, and they propose a localization method over different smartphones. It eliminates the impact of different handsets on RSSI. WiFi fingerprinting [19] is based on the RSSI associated with each wireless access point (APs) and is compared to a fingerprint database [20]. This fingerprint database contains a set of previously-recordedfingerprints at known reference points. The location of the target is usually determined by calculating the distance or fingerprints collected by the device and the fingerprints contained in the reference database [21]. However, there is an important disadvantage that the WiFi signals are affected by a number of factors, including changes in personnel activities and environmental facilities. Moreover,the hardware properties of APs also have a serious impact on RSSI and affect the performance of an indoor localization system. At present, some researchers have begun to discuss how to select an appropriate AP for positioning. [PERSON]; et al. [22] discusses a method of selecting APs for indoor localization. An important goal of indoor location estimation systems is to increase the estimation accuracy while reducing the power consumption. Choosing a suitable AP can reduce the power consumption of the AP and, at the same time, achieve a better positioning effect. For example, in underground mines, the environment is complicated and changeable, and when it changes, it will lead to the mutation of RSSI [23]. Moreover, considering the construction conditions of underground mines or unforeseen emergencies, there are potential safety hazards in the physical equipment in the location environment. When an AP is impaired, the RSSI of the AP loses the original transmission characteristics. Larger localization errors caused by these disturbances are more serious, especially for emergency rescue and target tracking in the current situation, which will lead to the target not being able to be accurately located. Figure 1 depicts the scenario of using impaired APs to locate when environmental changes occur. The impaired APs may be caused by plenty of factors, including earthquakes, explosions or just regular maintenance. In this paper, we describe the localization problem when there are impaired APs by using a mine collapse scenario. As shown in Figure 1, when the environment changes, APs are impaired and do not work properly, and if you cannot identify impaired APs in time, it will continue to use the RSSI of the impaired APs to locate. The RSSI of the impaired APs will be mutated, making it poorly matched with the fingerprint database and resulting in incorrect location information. In the case of emergency rescue, giving the wrong target location will mislead the rescue work and miss the best time to rescue. In view of the above problems, this paper analyzes the known WiFi fingerprinting methods for indoor localization. We examined various aspects of WiFi fingerprinting, including impaired APs and changes of the localization environment. We analyzed the RSSI characteristics of impaired APs.