Jung, Oliver and Smith, Paul and Magin, Julian and Reuter, Lenhard (2019) Anomaly Detection in Smart Grids based on Software Defined Networks. In: SMARTGREENS 2019 - Proceedings of the 8th International Conference on Smart Cities and Green ICT Systems. SMARTGREENS 2019 - Proceedings of the 8th International Conference on Smart Cities and Green ICT Systems . UNSPECIFIED, pp. 157-164. ISBN 9789897583735
Full text not available from this repository.Abstract
Software-defined networking (SDN) is a networking architecture that increasingly receives attention from power grid operators. The basic principle is the separation of the packet forwarding data plane and the central controller implemented in software that provides a programmable network control plane. SDN can provide various functions that facilitate the operation of smart grid communication networks, as it can support network management, quality of service (QoS) enforcement, network security, and network slicing. Due to periodical updates of the central controller, a real-time view of the network is available that allows for detecting attacks like e.g. denial-of-service (DoS) attack or network scanning. These kinds of attacks can be detected by applying anomaly detection mechanisms on the gathered information. In this position paper, we highlight the benefits SDN can bring to smart grids, address the implications of SDN on network security, and finally describe how information collected by a popular OpenFlow SDN controller can be used to detect attacks in smart grid communication networks.