Intrusion Detection with Unsupervised Techniques for Network Management Protocols over Smart Grids

Abstract

The present research work focuses on overcoming cybersecurity problems in the Smart Grid. Smart Grids must have feasible data capture and communications infrastructure to be able to manage the huge amounts of data coming from sensors. To ensure the proper operation of next-generation electricity grids, the captured data must be reliable and protected against vulnerabilities and possible attacks. The contribution of this paper to the state of the art lies in the identification of cyberattacks that produce anomalous behaviour in network management protocols. A novel neural projectionist technique (Beta Hebbian Learning, BHL) has been employed to get a general visual representation of the traffic of a network, making it possible to identify any abnormal behaviours and patterns, indicative of a cyberattack. This novel approach has been validated on 3 different datasets, demonstrating the ability of BHL to detect different types of attacks, more effectively than other state-of-the-art methods.

A Smart Grid AMI Intrusion Detection Strategy Based on Extreme Learning Machine

“…In a smart grid, because the advanced measurement system is connected to the internet and is susceptible to network intrusion, the advanced measurement system can be specifically divided into a three-layer network model: The first-level network is composed of smart meters and controllable appliances, which is susceptible to DoS and probing attacks; the second-level network is composed of the network before the smart meter and the concentrator, which is susceptible to user-to-root (U2R) attacks; the third-level network is composed of the network between the concentrator and the data processing center and is susceptible to remote-to-login (R2L) attacks [4]. In response to these four types of network attacks, this paper selects the KDDCUP99 dataset [44] for verification experiments, which can fully represent the IDS situation that AMI may encounter.…”

“…The smart grid is composed of two parts: power distribution networks and communication networks. The communication network is responsible for communication between various devices [4]. Since the communication network is often connected to a computer, it brings many new security issues.…”

Implementación virtual de prácticas de asignaturas de control como alternativa a las prácticas de laboratorio presenciales

“…Es por ello que, una alternativa interesante a los laboratorios reales son los laboratorios virtuales. Hoy en día, muchos de los sistemas basados en técnicas de inteligencia artificial como los que se explican en [31,1,9,17,39,7,28,26,33,13,45,29,36,40,44,34,27,4,47,4,16,14] se pueden verificar, en las primeras fases de diseño, mediante este tipo de laboratorios.…”

Solar Thermal Collector Output Temperature Prediction by Hybrid Intelligent Model for Smartgrid and Smartbuildings Applications and Optimization

“…The definition of the term smart city is under constant review [2,3]. Taking this fact into account, a smart city could be described as a city that uses the potential of technology and innovation, along with other resources that help make effective the use of this potential, promotes sustainable development, and ultimately, improves the quality of life of its citizens [4][5][6].…”