  Recent literature has shown that the control of False Discovery Rate (FDR)
for distributed detection in wireless sensor networks (WSNs) can provide
substantial improvement in detection performance over conventional design
methodologies. In this paper, we further investigate system design issues in
FDR based distributed detection. We demonstrate that improved system design may
be achieved by employing the Kolmogorov-Smirnov distance metric instead of the
deflection coefficient, as originally proposed in Ray&VarshneyAES11. We also
analyze the performance of FDR based distributed detection in the presence of
Byzantines. Byzantines are malicious sensors which send falsified information
to the Fusion Center (FC) to deteriorate system performance. We provide
analytical and simulation results on the global detection probability as a
function of the fraction of Byzantines in the network. It is observed that the
detection performance degrades considerably when the fraction of Byzantines is
large. Hence, we propose an adaptive algorithm at the FC which learns the
Byzantines' behavior over time and changes the FDR parameter to overcome the
loss in detection performance. Detailed simulation results are provided to
demonstrate the robustness of the proposed adaptive algorithm to Byzantine
attacks in WSNs.
