Analysis of location spoofing identification in cellular networks

Abstract

Location spoofing is considered as a serious threat to positioning and location based services in wireless networks. Existing identification methods for location spoofing have focused primarily on wireless sensor networks. These methods may not be applicable in cellular networks due to the following two limitations: (i) relying on accurate distance measurement; (ii) incapable of dealing with bad propagation conditions. To address these two issues, we carry out an analysis of location spoofing based on angle-of-arrival (AOA) and time-difference-of-arrival (TDOA) measurement models, two commonly used signal measurement models in cellular networks, in bad propagation conditions with large measurement errors. Our analysis shows that AOA model is more robust to location spoofing in noisy conditions.