Home // CYBER 2020, The Fifth International Conference on Cyber-Technologies and Cyber-Systems // View article
Authors:
Eric Veith
Stephan Balduin
Nils Wenninghoff
Martin Tröschel
Lars Fischer
Astrid Nieße
Thomas Wolgast
Richard Sethmann
Bastian Fraune
Torben Woltjen
Keywords: Cyber-Physical Systems Analysis; Distributed Artificial Intelligence; Reinforcement Learning; ICT Security; Market Design.
Abstract:
Modern Cyber-Physical Systems (CPSs), such as our energy infrastructure, are becoming increasingly complex: An ever-higher share of Artificial Intelligence (AI)-based technologies use the Information and Communication Technology (ICT) facet of energy systems for operation optimization, cost efficiency, and to reach CO2 goals worldwide. At the same time, markets with increased flexibility and ever shorter trade horizons enable the multi-stakeholder situation that is emerging in this setting. These systems still form critical infrastructures that need to perform with highest reliability. However, today's CPSs are becoming too complex to be analyzed in the traditional monolithic approach, where each domain, e.g., power grid and ICT, as well as the energy market, are considered as separate entities while ignoring dependencies and side-effects. To achieve an overall analysis, we introduce the concept for an application of distributed artificial intelligence as a self-adaptive analysis tool that is able to analyze the dependencies between domains in CPSs by attacking them. It eschews pre-configured domain knowledge, instead exploring the CPS domains for emergent risk situations and exploitable loopholes in codices, with a focus on rational market actors that exploit the system while still following the market rules.
Pages: 86 to 93
Copyright: Copyright (c) IARIA, 2020
Publication date: October 25, 2020
Published in: conference
ISSN: 2519-8599
ISBN: 978-1-61208-818-1
Location: Nice, France
Dates: from October 25, 2020 to October 29, 2020