Daniel Amyot
Professor
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About
Daniel Amyot is a Professor at the University of Ottawa in Canada. His research areas include automated generation of smart contract code, compliance technologies in data supply chains, and cybersecurity concerns for transactive energy markets. He has authored recent articles on the checking of legal contract properties and the application of requirements engineering to sustain human health. Additionally, his work encompasses innovative approaches to data aggregation in smart grids and the use of robotic process automation.
Articles (18)
Year:
2025
Year:
2025
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2025
Year:
2025
The transactive energy market is an emerging development in energy economics built on advanced metering infrastructure. Data generated in this context is often required for market operations, while also being privacy sensitive. This dual concern has necessitated the development of various methods of obfuscation in order to maintain privacy while still facilitating operations. While data aggregation is a common approach in this context, many of the existing aggregation methods rely on additional network components or lack flexibility. In this paper, we introduce Cyclic Homomorphic Encryption Aggregation (CHEA), a secure aggregation protocol that eliminates the need for additional network components or complicated key distribution schemes, while providing additional capabilities compared to similar protocols. We validate our scheme with formal security analysis as well as a software simulation of a transactive energy network running the scheme. Results indicate that CHEA performs well in comparison to similar works, with minimal communication overheads. Additionally, CHEA retains all standard security properties held by other aggregation schemes, while improving flexibility and reducing infrastructural requirements. Our scheme operates on similar assumptions as other works, but current smart metering hardware lags in terms of processing power, making the scheme infeasible on the current generation of hardware. However, these capabilities should quickly advance to an accommodating state. With this in mind, and given the results, we believe CHEA is a strong candidate for aggregating transactive energy data.
Year:
2024
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2024
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2023
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2023
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2023
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2023
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2023
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2022
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2022
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2022
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2022
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2022
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2022
Year:
2021
Collaborators (6)
Malak Baslyman
-
Yngve Lamo
Western Norway University of Applied Sciences
Gregory Richards
University of Ottawa
John Mylopoulos
University of Ottawa
Ita Richardson
University of Limerick
Lysanne Lessard
Associate Professor
University of Ottawa
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