Porcu, Daniele; Castro, Sonia; Otura, Borja; Encinar, Paula; Chochliouros, Ioannis; Ciornei, Irina; Hadjidemetriou, Lenos; Ellinas, Georgios; Santiago, Rita; Grigoriou, Elisavet; others,
In: Energies, vol. 15, no. 3, pp. 839, 2022.
As the complexity of electric systems increases, so does the required effort for the monitoring and management of grid operations. To solve grid performance issues, smart grids require the exchange of higher volumes of data, high availability of the telecommunication infrastructure, and very low latency. The fifth generation (5G) mobile network seems to be the most promising technology to support such requirements, allowing utilities to have dedicated virtual slices of network resources to maximize the service availability in case of network congestions. Regarding this evolving scenario, this work presents the Smart5Grid project vision on how 5G can support the energy vertical industry for the fast deployment of innovative digital services. Specifically, this work introduces the concept of network applications (NetApps), a new paradigm of virtualization that are envisioned to facilitate the creation of a new market for information technology (IT), small and medium enterprises (SMEs), and startups. This concept, and the open architecture that facilitates its implementation, is showcased by four real-life 5G-enabled demonstrators: (1) automatic fault detection in a medium voltage (MV) grid in Italy, (2) real-time safety monitoring for operators in high voltage (HV) substations in Spain, (3) remote distributed energy resources (DER) monitoring in Bulgaria, and (4) wide area monitoring in a cross-border scenario between Greece and Bulgaria. View Full-Text
Chochliouros, Ioannis P; Porcu, Daniele; Castro, Sonia; Otura, Borja; Encinar, Paula; Corsi, Antonello; Ciornei, Irina; Santiago, Rita; Antonopoulos, Angelos; Cadenelli, Nicola; others,
In: IFIP International Conference on Artificial Intelligence Applications and Innovations, pp. 134–147, Springer 2022.
Based on the original framework of the Smart5Grid EU-funded project, the present paper examines some fundamental features of the related platform that can be able to affect 5G implementation as well as the intended NetApps. Thus we examine: (i) the specific context of smart energy grids, enhanced by the inclusion of ICT and also supported by 5G connectivity; (ii) the cloud native context, together with the example of the cloud native VNF modelling, and; (iii) the MEC context as a 5G enabler for integrating management, control and orchestration processes. Each one is assessed compared to the state of the design and the implementation of the Smart5Grid platform. As a step further, we propose a preliminary framework for the definition of the NetApps, following to the way how the previous essential features are specifically incorporated within the project processes.
Grammatikis, Panagiotis Radoglou; Sarigiannidis, Panagiotis; Iturbe, Eider; Rios, Erkuden; Martinez, Saturnino; Sarigiannidis, Antonios; Efstathopoulos, Georgios; Spyridis, Yannis; Sesis, Achilleas; Vakakis, Nikolaos; Tzovaras, Dimitrios; Kafetzakis, Emmanouil; Giannoulakis, Ioannis; Tzifas, Michalis; Giannakoulias, Alkiviadis; Angelopoulos, Michail; Ramos, Francisco
In: Computer Networks, 2021.
The technological leap of smart technologies has brought the conventional electrical grid in a new digital era called Smart Grid (SG), providing multiple benefits, such as two-way communication, pervasive control and self-healing. However, this new reality generates significant cybersecurity risks due to the heterogeneous and insecure nature of SG. In particular, SG relies on legacy communication protocols that have not been implemented having cybersecurity in mind. Moreover, the advent of the Internet of Things (IoT) creates severe cybersecurity challenges. The Security Information and Event Management (SIEM) systems constitute an emerging technology in the cybersecurity area, having the capability to detect, normalise and correlate a vast amount of security events. They can orchestrate the entire security of a smart ecosystem, such as SG. Nevertheless, the current SIEM systems do not take into account the unique SG peculiarities and characteristics like the legacy communication protocols. In this paper, we present the Secure and PrivatE smArt gRid (SPEAR) SIEM, which focuses on SG. The main contribution of our work is the design and implementation of a SIEM system capable of detecting, normalising and correlating cyberattacks and anomalies against a plethora of SG application-layer protocols. It is noteworthy that the detection performance of the SPEAR SIEM is demonstrated with real data originating from four real SG use case (a) hydropower plant, (b) substation, (c) power plant and (d) smart home.
Porcu, Daniele; Chochliouros, Ioannis P; Castro, Sonia; Fiorentino, Giampaolo; Costa, Rui; Nodaros, Dimitrios; Koumaras, Vaios; Brasca, Fabrizio; di Pietro, Nicola; Papaioannou, George; others,
In: IFIP International Conference on Artificial Intelligence Applications and Innovations, pp. 7–20, Springer 2021.
The fast 5G deployment at global level influences a variety of vertical sectors and offers many opportunities for growth and innovation, drastically affecting modern economies. Among the major sectors where significant benefits are expected is the case of smart grid, where the management of energy demand is expected to become more efficient, leading to less investments. 5G inclusion and adaptation in smart grid will allow easier balance of energy load and reduction of electricity peaks, together with savings of energy cost. In the present work we introduce the innovative scope proposed by the Smart5Grid research project, aiming to complement contemporary energy distribution grids with access to 5G network resources through an open experimentation 5G platform and innovative Network Applications (NetApps). Smart5Grid administers four meaningful use cases for the energy vertical ecosystem, in order to demonstrate efficiency, resilience and elasticity provided by the 5G networks. In particular, each one among these use cases is presented and assessed as of its expected benefits and proposed novelties, based on the corresponding demonstration actions.
Sun, Zhonglin; Spyridis, Yannis; Sessis, Achilleas; Efstathopoulos, Georgios; Grigoriou, Elisavet; Lagkas, Thomas; Sarigiannidis, Panagiotis
In: 2021 IEEE Globecom Workshops (GC Wkshps), pp. 1–6, IEEE 2021.
Intentional islanding is a procedure to divide the electrical grid into several parts to guarantee the stability of a system in the case of failure. This study provides an unsupervised deep neural network to deal with the issue of intentional islanding. We propose to use a self-learning neural network to improve the generalisation performance of the islanding task. In addition, we use a merging technology to assign isolated buses to their neighbour's label. Experiments are carried out on several grid cases to illustrate the effect of our solution.
Radoglou-Grammatikis, Panagiotis; Sarigiannidis, Panagiotis; Efstathopoulos, George; Karypidis, Paris-Alexandros; Sarigiannidis, Antonios
In: Proceedings of the 15th International Conference on Availability, Reliability and Security, Association for Computing Machinery, Virtual Event, Ireland, 2020, ISBN: 9781450388337.
In this paper, an Intrusion Detection and Prevention System (IDPS) for the Distributed Network Protocol 3 (DNP3) Supervisory Control and Data Acquisition (SCADA) systems is presented. The proposed IDPS is called DIDEROT (Dnp3 Intrusion DetEction pReventiOn sysTem) and relies on both supervised Machine Learning (ML) and unsupervised/outlier ML detection models capable of discriminating whether a DNP3 network flow is related to a particular DNP3 cyberattack or anomaly. First, the supervised ML detection model is applied, trying to identify whether a DNP3 network flow is related to a specific DNP3 cyberattack. If the corresponding network flow is detected as normal, then the unsupervised/outlier ML anomaly detection model is activated, seeking to recognise the presence of a possible anomaly. Based on the DIDEROT detection results, the Software Defined Networking (SDN) technology is adopted in order to mitigate timely the corresponding DNP3 cyberattacks and anomalies. The performance of DIDEROT is demonstrated using real data originating from a substation environment.
Grammatikis, Panagiotis Radoglou; Sarigiannidis, Panagiotis; Iturbe, Eider; Rios, Erkuden; Sarigiannidis, Antonios; Nikolis, Odysseas; Ioannidis, Dimosthenis; Machamint, Vasileios; Tzifas, Michalis; Giannakoulias, Alkiviadis; Angelopoulos, Michail; Papadopoulos, Anastasios; Ramos, Francisco
Secure and Private Smart Grid: The SPEAR Architecture (Inproceedings)
In: 2020 6th IEEE International Conference on Network Softwarization (NetSoft), pp. 450-456, 2020.
Information and Communication Technology (ICT) is an integral part of Critical Infrastructures (CIs), bringing both significant pros and cons. Focusing our attention on the energy sector, ICT converts the conventional electrical grid into a new paradigm called Smart Grid (SG), providing crucial benefits such as pervasive control, better utilisation of the existing resources, self-healing, etc. However, in parallel, ICT increases the attack surface of this domain, generating new potential cyberthreats. In this paper, we present the Secure and PrivatE smArt gRid (SPEAR) architecture which constitutes an overall solution aiming at protecting SG, by enhancing situational awareness, detecting timely cyberattacks, collecting appropriate forensic evidence and providing an anonymous cybersecurity information-sharing mechanism. Operational characteristics and technical specifications details are analysed for each component, while also the communication interfaces among them are described in detail.
Pliatsios, Dimitrios; Sarigiannidis, Panagiotis; Lagkas, Thomas; Sarigiannidis, Antonios G
In: IEEE Communications Surveys Tutorials, vol. 22, no. 3, pp. 1942-1976, 2020.
Supervisory Control and Data Acquisition (SCADA) systems are the underlying monitoring and control components of critical infrastructures, such as power, telecommunication, transportation, pipelines, chemicals and manufacturing plants. Legacy SCADA systems operated on isolated networks, that made them less exposed to Internet threats. However, the increasing connection of SCADA systems to the Internet, as well as corporate networks, introduces severe security issues. Security considerations for SCADA systems are gaining higher attention, as the number of security incidents against these critical infrastructures is increasing. In this survey, we provide an overview of the general SCADA architecture, along with a detailed description of the SCADA communication protocols. Additionally, we discuss certain high-impact security incidents, objectives, and threats. Furthermore, we carry out an extensive review of the security proposals and tactics that aim to secure SCADA systems. We also discuss the state of SCADA system security. Finally, we present the current research trends and future advancements of SCADA security.
Efstathopoulos, Georgios; Grammatikis, Panagiotis Radoglou; Sarigiannidis, Panagiotis; Argyriou, Vasilis; Sarigiannidis, Antonios; Stamatakis, Konstantinos; Angelopoulos, Michail K; Athanasopoulos, Solon K
Operational Data Based Intrusion Detection System for Smart Grid (Inproceedings)
In: 2019 IEEE 24th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD), pp. 1-6, 2019.
With the rapid progression of Information and Communication Technology (ICT) and especially of Internet of Things (IoT), the conventional electrical grid is transformed into a new intelligent paradigm, known as Smart Grid (SG). SG provides significant benefits both for utility companies and energy consumers such as the two-way communication (both electricity and information), distributed generation, remote monitoring, self-healing and pervasive control. However, at the same time, this dependence introduces new security challenges, since SG inherits the vulnerabilities of multiple heterogeneous, co-existing legacy and smart technologies, such as IoT and Industrial Control Systems (ICS). An effective countermeasure against the various cyberthreats in SG is the Intrusion Detection System (IDS), informing the operator timely about the possible cyberattacks and anomalies. In this paper, we provide an anomaly-based IDS especially designed for SG utilising operational data from a real power plant. In particular, many machine learning and deep learning models were deployed, introducing novel parameters and feature representations in a comparative study. The evaluation analysis demonstrated the efficacy of the proposed IDS and the improvement due to the suggested complex data representation.