Security Baseline for Substation Automation Systems.

The use of information technology and the automation of control systems in the energy sector enables a more efficient transmission and distribution of electricity. However, in addition to the many benefits that the deployment of intelligent and largely autonomous systems brings, it also carries risks associated with information and cyber security breaches. Technology systems form a specific and critical communication infrastructure, in which powerful control elements integrating IoT principles and IED devices are present. It also contains intelligent access control systems such as RTU, IDE, HMI, and SCADA systems that provide communication with the data and control center on the outer perimeter. Therefore, the key question is how to comprehensively protect these specialized systems and how to approach security implementation projects in this area. To establish rules, procedures, and techniques to ensure the cyber security of smart grid control systems in the energy sector, it is necessary to understand the security threats and bring appropriate measures to ensure the security of energy distribution. Given the use of a wide range of information and industrial technologies, it is difficult to protect energy distribution systems using standard constraints to protect common IT technologies and business processes. Therefore, as part of a comprehensive approach to cyber security, specifics such as legislative framework, technological constraints, international standards, specialized protocols or company processes, and many others need to be considered. Therefore, the key question is how to comprehensively protect these specialized systems and how to approach security implementation projects in this area. In this article, a basic security concept for control systems of power stations, which are part of the power transmission and distribution system, is presented based on the Smart Grid domain model with emphasis on substation intelligence, according to the Purdue model. The main contribution of the paper is the comprehensive design of mitigation measures divided into mandatory and recommended implementation based on the standards defined within the MITRE ATT&CK matrix specified, concerning the specifications of intelligent distribution substations. The proposed and industry-tested solution is mapped to meet the international security standards ISO 27001 and national legislation reflecting the requirements of NIS2. This ensures that the security requirements will be met when implementing the proposed Security Baseline.

Deformation and seismicity decline before the 2021 Fagradalsfjall eruption.

Increased rates of deformation and seismicity are well-established precursors to volcanic eruptions, and their interpretation forms the basis for eruption warnings worldwide. Rates of ground displacement and the number of earthquakes escalate before many eruptions1-3, as magma forces its way towards the surface. However, the pre-eruptive patterns of deformation and seismicity vary widely. Here we show how an eruption beginning on 19 March 2021 at Fagradalsfjall, Iceland, was preceded by a period of tectonic stress release ending with a decline in deformation and seismicity over several days preceding the eruption onset. High rates of deformation and seismicity occurred from 24 February to mid-March in relation to gradual emplacement of an approximately 9-km-long magma-filled dyke, between the surface and 8 km depth (volume approximately 34 × 106 m3), as well as the triggering of strike-slip earthquakes up to magnitude MW 5.64. As stored tectonic stress was systematically released, there was less lateral migration of magma and a reduction in both the deformation rates and seismicity. Weaker crust near the surface may also have contributed to reduced seismicity, as the depth of active magma emplacement progressively shallowed. This demonstrates that the interaction between volcanoes and tectonic stress as well as crustal layering need to be fully considered when forecasting eruptions.

Automated microseismic event location using Master-Event Waveform Stacking.

Accurate and automated locations of microseismic events are desirable for many seismological and industrial applications. The analysis of microseismicity is particularly challenging because of weak seismic signals with low signal-to-noise ratio. Traditional location approaches rely on automated picking, based on individual seismograms, and make no use of the coherency information between signals at different stations. This strong limitation has been overcome by full-waveform location methods, which exploit the coherency of waveforms at different stations and improve the location robustness even in presence of noise. However, the performance of these methods strongly depend on the accuracy of the adopted velocity model, which is often quite rough; inaccurate models result in large location errors. We present an improved waveform stacking location method based on source-specific station corrections. Our method inherits the advantages of full-waveform location methods while strongly mitigating the dependency on the accuracy of the velocity model. With this approach the influence of an inaccurate velocity model on the results is restricted to the estimation of travel times solely within the seismogenic volume, but not for the entire source-receiver path. We finally successfully applied our new method to a realistic synthetic dataset as well as real data.