@conference {846,
	title = {Design of data-injection adversarial attacks against spatial field detectors},
	booktitle = {IEEE Workshop on Statistical Signal Processing (SSP)},
	year = {2016},
	month = {06/2016},
	address = {Palma de Mallorca, Spain},
	abstract = {<p><span style="color: rgb(51, 51, 51); font-family: Arial, Georgia, \&quot;Bitstream Charter\&quot;, serif; font-size: 16px; line-height: 24px; background-color: rgb(255, 255, 255);">Data-injection attacks on spatial field detection corrupt a subset of measurements to cause erroneous decisions. We consider a centralized decision scheme exploiting spatial field smoothness to overcome lack of knowledge on system parameters such as noise variance. We obtain closed-form expressions for system performance and investigate strategies for an intruder injecting false data in a fraction of the sensors in order to reduce the probability of detection. The problem of determining the most vulnerable subset of sensors is also analyzed.</span></p>},
	keywords = {adversarial signal processing, compass, wsn},
	author = {R. L{\'o}pez-Valcarce and Daniel Romero}
}
