The Experts below are selected from a list of 15 Experts worldwide ranked by ideXlab platform
Kulvinder Lotay - One of the best experts on this subject based on the ideXlab platform.
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secure Decentralized Energy Resource management using the ethereum blockchain
Trust Security And Privacy In Computing And Communications, 2018Co-Authors: Casimer Decusatis, Kulvinder LotayAbstract:While blockchain services hold great promise to improve many different industries, there are significant cybersecurity concerns which must be addressed. In this paper, we investigate security considerations for an Ethereum blockchain hosting a distributed Energy management application. We have simulated a microgrid with ten buildings in the northeast U.S., and results of the transaction distribution and electricity utilization are presented. We also present the effects on Energy distribution when one or two smart meters have their identities corrupted. We then propose a new approach to digital identity management that would require smart meters to authenticate with the blockchain ledger and mitigate identity-spoofing attacks. Applications of this approach to defense against port scans and DDoS, attacks are also discussed.
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TrustCom/BigDataSE - Secure, Decentralized Energy Resource Management Using the Ethereum Blockchain
2018 17th IEEE International Conference On Trust Security And Privacy In Computing And Communications 12th IEEE International Conference On Big Data S, 2018Co-Authors: Casimer Decusatis, Kulvinder LotayAbstract:While blockchain services hold great promise to improve many different industries, there are significant cybersecurity concerns which must be addressed. In this paper, we investigate security considerations for an Ethereum blockchain hosting a distributed Energy management application. We have simulated a microgrid with ten buildings in the northeast U.S., and results of the transaction distribution and electricity utilization are presented. We also present the effects on Energy distribution when one or two smart meters have their identities corrupted. We then propose a new approach to digital identity management that would require smart meters to authenticate with the blockchain ledger and mitigate identity-spoofing attacks. Applications of this approach to defense against port scans and DDoS, attacks are also discussed.
Casimer Decusatis - One of the best experts on this subject based on the ideXlab platform.
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secure Decentralized Energy Resource management using the ethereum blockchain
Trust Security And Privacy In Computing And Communications, 2018Co-Authors: Casimer Decusatis, Kulvinder LotayAbstract:While blockchain services hold great promise to improve many different industries, there are significant cybersecurity concerns which must be addressed. In this paper, we investigate security considerations for an Ethereum blockchain hosting a distributed Energy management application. We have simulated a microgrid with ten buildings in the northeast U.S., and results of the transaction distribution and electricity utilization are presented. We also present the effects on Energy distribution when one or two smart meters have their identities corrupted. We then propose a new approach to digital identity management that would require smart meters to authenticate with the blockchain ledger and mitigate identity-spoofing attacks. Applications of this approach to defense against port scans and DDoS, attacks are also discussed.
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TrustCom/BigDataSE - Secure, Decentralized Energy Resource Management Using the Ethereum Blockchain
2018 17th IEEE International Conference On Trust Security And Privacy In Computing And Communications 12th IEEE International Conference On Big Data S, 2018Co-Authors: Casimer Decusatis, Kulvinder LotayAbstract:While blockchain services hold great promise to improve many different industries, there are significant cybersecurity concerns which must be addressed. In this paper, we investigate security considerations for an Ethereum blockchain hosting a distributed Energy management application. We have simulated a microgrid with ten buildings in the northeast U.S., and results of the transaction distribution and electricity utilization are presented. We also present the effects on Energy distribution when one or two smart meters have their identities corrupted. We then propose a new approach to digital identity management that would require smart meters to authenticate with the blockchain ledger and mitigate identity-spoofing attacks. Applications of this approach to defense against port scans and DDoS, attacks are also discussed.
Geoff James - One of the best experts on this subject based on the ideXlab platform.
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SASO - Clustering Distributed Energy Resources for Large-Scale Demand Management
First International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2007), 2007Co-Authors: E. Ogston, Astrid Zeman, Mikhail Prokopenko, Geoff JamesAbstract:Managing demand for electrical Energy allows generation facilities to be run more efficiently. Current systems allow for management between large industrial consumers. There is, however, an increasing trend to decentralize Energy Resource management and push it to the level of individual households, or even appliances. In this work we investigate the suitability of using adaptive clustering to improve the scalability of Decentralized Energy Resource management systems by appropriately partitioning Resources. We review the area of distributed Energy Resource management and propose a simple yet realistic model to study the problem. Simulations using this model show that straightforward clustering and distributed planning methods allow systems to scale, but may be limited to only a few hundred- thousand appliances. Results indicate that there is an opportunity to apply adaptive clustering techniques in order to discover more advanced grouping criteria that would enable groups to change as appliances' behavior changes. The simulations further suggest that even an extremely limited exchange of information between clusters can greatly improve management solutions.
E. Ogston - One of the best experts on this subject based on the ideXlab platform.
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SASO - Clustering Distributed Energy Resources for Large-Scale Demand Management
First International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2007), 2007Co-Authors: E. Ogston, Astrid Zeman, Mikhail Prokopenko, Geoff JamesAbstract:Managing demand for electrical Energy allows generation facilities to be run more efficiently. Current systems allow for management between large industrial consumers. There is, however, an increasing trend to decentralize Energy Resource management and push it to the level of individual households, or even appliances. In this work we investigate the suitability of using adaptive clustering to improve the scalability of Decentralized Energy Resource management systems by appropriately partitioning Resources. We review the area of distributed Energy Resource management and propose a simple yet realistic model to study the problem. Simulations using this model show that straightforward clustering and distributed planning methods allow systems to scale, but may be limited to only a few hundred- thousand appliances. Results indicate that there is an opportunity to apply adaptive clustering techniques in order to discover more advanced grouping criteria that would enable groups to change as appliances' behavior changes. The simulations further suggest that even an extremely limited exchange of information between clusters can greatly improve management solutions.
Astrid Zeman - One of the best experts on this subject based on the ideXlab platform.
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SASO - Clustering Distributed Energy Resources for Large-Scale Demand Management
First International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2007), 2007Co-Authors: E. Ogston, Astrid Zeman, Mikhail Prokopenko, Geoff JamesAbstract:Managing demand for electrical Energy allows generation facilities to be run more efficiently. Current systems allow for management between large industrial consumers. There is, however, an increasing trend to decentralize Energy Resource management and push it to the level of individual households, or even appliances. In this work we investigate the suitability of using adaptive clustering to improve the scalability of Decentralized Energy Resource management systems by appropriately partitioning Resources. We review the area of distributed Energy Resource management and propose a simple yet realistic model to study the problem. Simulations using this model show that straightforward clustering and distributed planning methods allow systems to scale, but may be limited to only a few hundred- thousand appliances. Results indicate that there is an opportunity to apply adaptive clustering techniques in order to discover more advanced grouping criteria that would enable groups to change as appliances' behavior changes. The simulations further suggest that even an extremely limited exchange of information between clusters can greatly improve management solutions.
