Adversarial indoor signal detection

We consider the problem of accurately detecting signals from contraband WiFi devices. Source locations may be selected in a worst-case fashion from within an indoor structure, such as a correctional facility. The structure layout is known, but inaccessible prior to deployment, and only a small number of detectors are available for sensing these signals. Our approach treats this setting as a covering problem, where the aim is to achieve a high probability of detection at each of the grid points of the terrain. Unlike prior approaches, we employ (1) a variant of the maximum coverage problem, which allows us to account for aggregate coverage by several detectors, and (2) a state-of-the-art commercial wireless simulator to provide SINR measurements that inform our problem instances. This approach is formulated as a mathematical program to which additional constraints are added to limit the number of detectors. Solving the program produces a placement of detectors whose performance is then evaluated for classifier accuracy. We present preliminary results, combining both simulation data and real-world data to evaluate the performance our approach against two competitors inspired by the literature.