Extending a Trust model for Energy Trading with Cyber-Attack Detection
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This paper explores the concept of the local energy markets and, in particular, the need for trust and security in the negotiations necessary for this type of market. A multi-agent system is implemented to simulate the local energy market, and a trust model is proposed to evaluate the proposals sent by the participants, based on forecasting mechanisms that try to predict their expected behavior. A cyber-attack detection model is also implemented using several supervised classification techniques. Two case studies were carried out, one to evaluate the performance of the various classification methods using the IoT-23 cyber-attack dataset; and another one to evaluate the performance of the developed trust mode.
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2009 ◽
Vol E92-A
(7)
◽
pp. 1585-1592
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2021 ◽
Vol 17
(1)
◽
pp. 650-658
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