Conference paper Open Access

Big Data against Security Threats: The SPEAR Intrusion Detection System

Dimitrios Pliatsios; Panagiotis Sarigiannidis; Konstantinos Psannis; Sotirios K. Goudos; Vasileios Vitsas; Ioannis Moscholios

The environmental concerns, the limited availability of conventional energy sources, the integration of alternative energy sources and the increasing number of power-demanding appliances change the way electricity is generated and distributed. Smart Grid (SG) is an appealing concept, which was developed in response to the emerging issues of electricity generation and distribution. By leveraging the latest advancements of Information and Communication Technologies (ICT), it offers significant benefits to energy providers, retailers and consumers. Nevertheless, SG is vulnerable to cyber attacks, that could cause critical economic and ecological consequences. Traditional Intrusion Detection Systems (IDSs) are becoming less efficient in detecting and mitigating cyberattacks, due to their limited capabilities of analyzing the exponentially increasing volume of network traffic. In this paper, we present the Secure and PrivatE smArt gRid (SPEAR) platform, which features a Big Data enabled IDS that timely detects and identifies cyber attacks against SG components. In order to validate the efficiency of the SPEAR platform regarding the protection of critical infrastructure, we installed the platform in a small wind power plant.

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