  During the last two decades, distributed energy systems, especially renewable
energy sources (RES), have become more economically viable with increasing
market share and penetration levels on power systems. In addition to
decarbonization and decentralization of energy systems, digitalization has also
become very important. The use of artificial intelligence (AI), advanced
optimization algorithms, Industrial Internet of Things (IIoT), and other
digitalization frameworks makes modern power system assets more intelligent,
while vulnerable to cybersecurity risks. This paper proposes the concept of the
Internet of Predictable Things (IoPT) that incorporates advanced data analytics
and machine learning methods to increase the resiliency of cyber-physical
systems against cybersecurity risks. The proposed concept is demonstrated using
a cyber-physical system testbed under a variety of cyber attack scenarios as a
proof of concept (PoC).
