Cyber-Attacks and Mitigation in Blockchain Based Transactive Energy Systems
June 2020·
,
,,
Carlos Barreto
Taha Eghtesad
Scott Eisele
Aron Laszka
Abhishek Dubey
Xenofon Koutsoukos
Abstract
Power grids are undergoing major changes due to the rapid adoption of intermittent renewable energy resources and the increased availability of energy storage devices. These trends drive smart-grid operators to envision a future where peerto-peer energy trading occurs within microgrids, leading to the development of Transactive Energy Systems. Blockchains have garnered significant interest from both academia and industry for their potential application in decentralized TES, in large part due to their high level of resilience. In this paper, we introduce a novel class of attacks against blockchain based TES, which target the gateways that connect market participants to the system. We introduce a general model of blockchain based TES and study multiple threat models and attack strategies. We also demonstrate the impact of these attacks using a testbed based on GridLAB-D and a private Ethereum network. Finally, we study how to mitigate these attack.
Type
Venue
3rd IEEE International Conference on Industrial Cyber-Physical Systems (ICPS 2020), 129–136
Authors
Ph.D. 2026
Taha Eghtesad joined the Applied Artificial Intelligence Lab as a Ph.D. student in Fall 2018 and received his Ph.D.
in 2026 under the supervision of Dr. Aron Laszka. He received a B.S. degree in Computer Engineering, with a minor in
Software Engineering, from Shahid Beheshti University, Tehran, Iran. His research lies at the intersection of
machine learning, game theory, cyber-physical systems, and systems security. In particular, his Ph.D. research
focused on using artificial intelligence and machine learning to make cyber-physical systems more secure.
Associate Professor
Aron Laszka is an Associate Professor in the College of Information Sciences and Technology at the Pennsylvania State University. Previously, he was an Assistant Professor at the University of Houston, a Research Assistant Professor at Vanderbilt University, and a Postdoctoral Scholar at the University of California, Berkeley.
His research interests revolve around artificial intelligence and cyber-physical systems, focusing on machine learning for decision making and optimization, with applications in smart and connected communities, critical infrastructure, and cybersecurity.
His research is funded by the National Science Foundation, the Department of Energy, the Department of Transportation, and other agencies.