  This paper addresses the problem of estimating an unknown static parameter by
a network of sensor nodes in a distributed manner over a directed communication
network in the presence of adversaries. We introduce an algorithm, Resilient
Estimation through Weight Balancing (REWB), which ensures that all the nodes,
both normal and malicious, asymptotically converge to the value to be estimated
provided less than half of them are affected by adversaries. We discuss how our
REWB algorithm is developed using the concepts of weight balancing of directed
graphs, and the consensus+innovations approach for linear estimation. Numerical
simulations are presented to show the performance of our algorithm over
directed graphs and its resilience to sensor attacks.
