Related papers: Adversarial Models Towards Data Availability and I…
In this paper, secure, remote estimation of a linear Gaussian process via observations at multiple sensors is considered. Such a framework is relevant to many cyber-physical systems and internet-of-things applications. Sensors make…
Today's power generation and distribution networks are quickly moving toward automated control and integration of renewable resources - a complex, integrated system termed the Smart Grid. A key component in planning and managing of Smart…
A class of data integrity attack, known as false data injection (FDI) attack, has been studied with a considerable amount of work. It has shown that with perfect knowledge of the system model and the capability to manipulate a certain…
The rapid development of information and communications technology has enabled the use of digital-controlled and software-driven distributed energy resources (DERs) to improve the flexibility and efficiency of power supply, and support grid…
Security in the fifth generation (5G) networks has become one of the prime concerns in the telecommunication industry. 5G security challenges come from the fact that 5G networks involve different stakeholders using different security…
Data analysis and monitoring on smart grids are jeopardized by attacks on cyber-physical systems. False data injection attack (FDIA) is one of the classes of those attacks that target the smart measurement devices by injecting malicious…
Gaussian random attacks that jointly minimize the amount of information obtained by the operator from the grid and the probability of attack detection are presented. The construction of the attack is posed as an optimization problem with a…
Attack detection problems in the smart grid are posed as statistical learning problems for different attack scenarios in which the measurements are observed in batch or online settings. In this approach, machine learning algorithms are used…
Real time operation of the power grid and synchronism of its different elements require accurate estimation of its state variables. Errors in state estimation will lead to sub-optimal Optimal Power Flow (OPF) solutions and subsequent…
An unobservable false data injection (FDI) attack on AC state estimation (SE) is introduced and its consequences on the physical system are studied. With a focus on understanding the physical consequences of FDI attacks, a bi-level…
In current Internet-of-Things (IoT) deployments, a mix of traditional IP networking and IoT specific protocols, both relying on the TCP protocol, can be used to transport data from a source to a destination. Therefore, TCP-specific attacks,…
This article focuses on cyber security threats from IoT-enabled energy smart appliances (ESAs) such as smart heat pumps, electric vehicle chargers, etc., to power grid operations. It presents an in-depth analysis of the demand side threats,…
A new paradigm of electricity generation at the distribution level, with renewable and alternative sources, is possible with microgrids. The main idea is to have microgrids deployed on low- or medium-voltage active distribution networks.…
The growth in the number of devices connected to the Internet of Things (IoT) poses major challenges in security. The integrity and trustworthiness of data and data analytics are increasingly important concerns in IoT applications. These…
The emergence of deep learning models has revolutionized various industries over the last decade, leading to a surge in connected devices and infrastructures. However, these models can be tricked into making incorrect predictions with high…
Recent massive failures in the power grid acted as a wake up call for all utilities and consumers. This leads to aggressive pursue a more intelligent grid which addresses the concerns of reliability, efficiency, security, quality and…
Reliable grid operation depends on accurate and timely telemetry, making modern power systems vulnerable to communication layer cyberattacks. This paper evaluates how Denial of Service (DoS), Denial of Data (DoD), and False Data Injection…
Effective detection of energy theft can prevent revenue losses of utility companies and is also important for smart grid security. In recent years, enabled by the massive fine-grained smart meter data, deep learning (DL) approaches are…
In this work we study the problem of State Estimation(SE) in large-scale, 3-phase coupled, unbalanced distribution systems. More specifically, we address the problem of including mixed real-time measurements, synchronized and…
Smart grid (SG) is a complex cyber-physical system that utilizes modern cyber and physical equipment to run at an optimal operating point. Cyberattacks are the principal threats confronting the usage and advancement of the state-of-the-art…