A trust evaluation model for secure data aggregation in smart grids infrastructures for smart cities

New technologies and automation systems have changed the traditional smart grid systems into new and integrated intelligent systems. These new smart systems are adopted for energy efficiency, demand and response, management and control, fault recovery, reliability and quality of services. With various benefits, smart grids have vulnerabilities due to open communication systems, and open infrastructures. Smart grids systems are based on real-time services, where privacy and security id one of the major challenge. In order to address these challenges and deal with security and privacy issues, we proposed a Trust Evaluation Model for Smart Grids (TEMSG) for secure data aggregation in smart grids and smart cities. This model tackles privacy and security issues such as data theft, denial of services, data privacy and inside and outside attacks and malware attacks. Machine learning methods are used to gather trust values and then estimate the imprecise information to secure the data aggregation in smart grids. Experiments are conducted to evaluate and analyze the proposed model in terms of detection rate, trustworthiness, and accuracy.