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Electrical Engineering and Systems Science > Systems and Control

arXiv:2101.07816 (eess)
[Submitted on 19 Jan 2021]

Title:Internet of Predictable Things (IoPT) Framework to Increase Cyber-Physical System Resiliency

Authors:Umit Cali, Murat Kuzlu, Vinayak Sharma, Manisa Pipattanasomporn, Ferhat Ozgur Catak
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Abstract: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).
Comments: 13 pages
Subjects: Systems and Control (eess.SY); Artificial Intelligence (cs.AI)
Cite as: arXiv:2101.07816 [eess.SY]
  (or arXiv:2101.07816v1 [eess.SY] for this version)
  https://doi.org/10.48550/arXiv.2101.07816

Submission history

From: Ferhat Ozgur Catak [view email]
[v1] Tue, 19 Jan 2021 19:01:56 UTC (991 KB)
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