Critical infrastructures like the power grid are at risk from increasing cyber threats due to high penetration of interconnected distributed energy resources (DER). Compromised DER endpoints can cause events, data breaches, communication loss, intentional device failures, and even cascading outages. To address these challenges, this paper explores cybersecurity issues in DER management systems (DERMS), including state-of-the-art reviews on architectures, communication protocols, access control privileges, data breaches, identity management policies, attacks such as false data injection, denial of service, distributed denial of service, malware, threats affecting data integrity, and network vulnerabilities. Realistic threat scenarios are outlined, followed by discussions on futuristic solutions like the zero trust framework. (read more)

Virtual power plants (VPPs) are used to manage and integrate renewable energy resources for better management and coordination. This integration, combined with modern communication technologies, offers several benefits for VPPs, such as improved interconnectedness between the energy assets, increased efficiency, and ease of management. The current article reviews current state-of-the-art security challenges in VPPs as well as the existing security solutions for securing them. Methods such as network segmentation, continuous monitoring, and encryption were analyzed along with emerging technologies such as blockchain, zero-trust, and federated learning. The findings show that the current solutions still work to some extent; however, with the introduction of new technologies, it is possible to increase related security levels in VPPs significantly. (read more)

Endpoint security solutions play a critical role in protecting an organization’s network and connected devices. When these security solutions have vulnerabilities, either intentional or unintentional, they can open the door to some serious cyber-attacks, potentially causing major disruptions. To stay ahead of threats, security providers regularly release updates or patches that not only improve performance, but also strengthen security. Sometimes, these updates can contain flaws and lead to some unintended consequences. A recent example of this is the Crowd-Strike incident, which caused a global service outage. This paper takes a closer look at what happened during the CrowdStrike incident, the services that were impacted, and the catastrophic aftermath. The release of a flawed update from Crowdstrike Falcon software caused 8.5M Windows devices to crash.(read more)

This study seeks to investigate the recent trends in Digital Twin (DT) technology and how it can be utilized to improve the existing security of vulnerable public water treatment and wastewater treatment facilities. The scope of this study explores the integration of DT in water utilities to understand the technology’s potential in improving security and enhancing system efficiency. The paper also presents the Operational Technology (OT) issues and an overview of the capability in all manners with which Digital Twins use can transform water utility operations. (read more)

Modern critical infrastructure such as an electric grid, uses information and communication technologies (ICT) to increase system performance. However, the integration of Distributed Energy Resources (DERs) and their interconnectedness to ICTs exposes them to different threat landscapes. To defend and mitigate cyberattacks targeting critical infrastructure, there is a critical need for robust situational awareness tool(s) and strategies. This paper reviews the existing work on the deployment of Transformer Neural Networks (TNN) in Intrusion Detection Units (IDUs) and Anomaly Detection (AD) applications. Additionally, the paper discusses specific stealthy attack scenarios and provides recommendations by mapping Confidentiality, Integrity, Availability, and Accountability (CIAA) properties to different attacks. (read more)

Digital transformation caused rapid automation and lots of changes in many sectors of the modern life. Unfortunately, the changes have been followed by cyber threats. Today, the actual types of cyber threat types cannot be counted easily as there is a wide variety of risk factors expanding still. There is an increased frequency of cyber threats in critical infrastructures and across all application sectors. Further, Artificial Intelligence expands this threat landscape to another new level by integrating sophisticated ways (eg, automated coding, deep fakes, social engineering) of manipulating or exploiting humans, systems or networks. There is immediate need to train the next generation cyber security workforce pipeline to address this skill gap in cyber security. (read more)

Solar flares reaching Earth from the Sun create geomagnetic storms upon their interaction with Earth’s magnetic field. This affects the atmosphere, causing effects such as the aurora borealis. It also leads to minor to significant disruptions in power grids and radio communications worldwide. Geomagnetic storms are measured using various indices, including solar wind parameters, K-index, and Disturbance Storm Time (DST). In this paper, machine learning models, such as Multi-linear regression (MLR), Random Forest regression (RFR), Support Vector Regression (SVR), Extreme gradient boosting(XGB), and Long Short-Term Memory(LSTM) models, are deployed, and their performance is compared. Of these, XGB performed best with an MAE value of 0.58 and an RMSE value of 0.7. (read more)

Adaptation of technologies such as the Internet of Things (IoT), Unmanned Aerial Vehicles (UAVs), and block chain in agriculture has revolutionized farming activities, offering several benefits such as increased efficiency, reduced costs, and improved crop yields. However, these advancements also have their fair share of security challenges, opening space for vulnerabilities that adversaries can exploit and compromising agricultural IoT networks, autonomous farming equipment, and vehicles. This may lead to compromised services and devices disrupting farming activities, causing losses to the farmers. This paper captures the state-of-the-art review of IoT-based precision farming systems, including the technological applications, cybersecurity challenges, and mitigation measures to secure the agricultural environment. (read more)

Soybean Cyst Nematode (SCN) is a serious pathogen in soybean production and contributes to annual economic losses of more than $1.5 billion (1996–2016) in the U.S. SCN is a microscopic thread-like nematode that burrows into the roots of soybean plants and typically cannot be identified above ground. The paper investigates multitude of variables such as NDVI from multi-spectral images, egg counts, and micro-nutrient composition (e.g., pH, nitrogen, phosphorus, potassium) across two SCN-prone field plots in Casselton/Prosper, North Dakota. The preliminary results indicate that NDVI is a good metric to track for SCN density population during planting, growing, and harvesting periods along with other historical ground truth data. Also, a contour plot using Empirical Bayesian Kriging (EBK) was designed by integrating NDVI and egg count data for co-tracking distribution changes. (read more)