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With today's growth of prosumers and renewable energy resources, it is inevitable to incorporate the demand-side approaches for reliable and sustainable grid operation. In this context, demand response is a promising technique facilitating the consumers to play a substantial role in the energy market by altering their energy consumption patterns in times of peak demand or other critical contingencies. However, effective demand response deployment faces numerous challenges including trust deficit among the concerned stakeholders. This paper addresses the mentioned issue by proposing a non-invasive load-shed authentication model for demand response applications, assisted by an improved event-based non-intrusive load monitoring approach. For the said purposes, an improved event detection algorithm and machine learning model: support vector machine with a combination of genetic algorithm and …