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

arXiv 2101.07816 ↗First posted 19 Jan 2021eess.SY cs.AI cs.SYcited by 0

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Abstract (arXiv)

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).

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 3 of its 47 references that are in the map. First posted on arXiv 19 Jan 2021.

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References · 3

  1. 2014Explaining and Harnessing Adversarial Examplescited by 7,364
  2. 2016Adversarial examples in the physical worldcited by 1,769
  3. 2015DeepFool: a simple and accurate method to fool deep neural networkscited by 1,318

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