Wasserstein Metric-Based Location Spoofing Attack Detection in WiFi Positioning Systems

Algorithm 1

Density-based spatial clustering of applications with noise.

(1)	Collect all WiFi APs in the environment as the points in the dataset
(2)	Estimate the Wasserstein metric between each pair of points in the dataset
(3)	Find the points in the -neighborhood of every point, and identify the core points with more than min_pts neighbors
(4)	Find the connected components of core points on the neighbor graph, ignoring all noncore points
(5)	Assign each noncore point to a nearby cluster if the cluster is an - neighborhood, otherwise assign it to noise
(6)	Mark the remaining noise points in the dataset as legitimate APs and the ones that have been clustered as fake APs