Elements of information theory
Elements of information theory
The Byzantine Generals Problem
ACM Transactions on Programming Languages and Systems (TOPLAS)
Distributed Detection and Data Fusion
Distributed Detection and Data Fusion
Fault Tolerance in Collaborative Sensor Networks for Target Detection
IEEE Transactions on Computers
Convex Optimization
On Distributed Fault-Tolerant Detection in Wireless Sensor Networks
IEEE Transactions on Computers
The good, bad and ugly: distributed detection of a known signal in dependent Gaussian noise
IEEE Transactions on Signal Processing
Designing secure sensor networks
IEEE Wireless Communications
Distributed Source Coding in the Presence of Byzantine Sensors
IEEE Transactions on Information Theory
Statistical en-route filtering of injected false data in sensor networks
IEEE Journal on Selected Areas in Communications
POSTER: Signal anomaly based attack detection in wireless sensor networks
Proceedings of the 2013 ACM SIGSAC conference on Computer & communications security
Hi-index | 35.68 |
Distributed detection in the presence of cooperative (Byzantine) attack is considered. It is assumed that a fraction of the monitoring sensors are compromised by an adversary, and these compromised (Byzantine) sensors are reprogrammed to transmit fictitious observations aimed at confusing the decision maker at the fusion center. For detection under binary hypotheses with quantized sensor observations, the optimal attacking distributions for Byzantine sensors that minimize the detection error exponent are obtained using a "water-filling" procedure. The smallest error exponent, as a function of the Byzantine sensor population, characterizes the power of attack. Also obtained is the minimum fraction of Byzantine sensors that destroys the consistency of detection at the fusion center. The case when multiple measurements are made at the remote nodes is also considered, and it is shown that the detection performance scales with the number of sensors differently from the number of observations at each sensor.