  Smart grids are large and complex cyber physical infrastructures that require
real-time monitoring for ensuring the security and reliability of the system.
Monitoring the smart grid involves analyzing continuous data-stream from
various measurement devices deployed throughout the system, which are
topologically distributed and structurally interrelated. In this paper, graph
signal processing (GSP) has been used to represent and analyze the power grid
measurement data. It is shown that GSP can enable various analyses for the
power grid's structured data and dynamics of its interconnected components.
Particularly, the effects of various cyber and physical stresses in the power
grid are evaluated and discussed both in the vertex and the graph-frequency
domains of the signals. Several techniques for detecting and locating cyber and
physical stresses based on GSP techniques have been presented and their
performances have been evaluated and compared. The presented study shows that
GSP can be a promising approach for analyzing the power grid's data.
