A survey of secure fingerprinting localization in wireless local area networks

Secure localization has gained considerable attention because position estimation is often required for location based applications. This problem becomes more important for wireless local area networks (WLANs), where the radio signals are susceptible to a variety of attacks due to the nature of the open medium. This paper proposes a survey of security positioning systems in WLANs. We classify secure positioning mechanisms into two categories: signal-based and model-based approaches. The former attempts to detect attacks and exclude them during positioning while the latter enhances localization schemes capable of tolerating attacks. This study examines three signal-based approaches, including median-based method, sensor selection, and RSM (Ration-based Signal strength Metric), and three model-based approaches, including cluster-based method, RWGH (Residual Weighting), and IDM (Inclusive Disjunction Model). We evaluate their robustness to attacks, positioning accuracy, and computational complexity. Simulation results show that the model-based techniques generally perform better robustness; However, the improvement is gained at the expense of degrading performance in an attack-free condition and higher computational overhead. This paper also investigates how the number of attacks impact these secure positioning algorithms.