相关论文: Analysis of Load-Altering Attacks Against Power Gr…

A significant challenge in energy system cyber security is the current inability to detect cyber-physical attacks targeting and originating from distributed grid-edge devices such as photovoltaics (PV) panels, smart flexible loads, and…

LoRaWAN enables massive connectivity for Internet-of-Things applications. Many published works employ stochastic geometry to derive outage models of LoRaWAN over fading channels assuming fixed transmit power and distance-based spreading…

In this paper, we consider the problem of attack-resilient state estimation, that is to reliably estimate the true system states despite two classes of attacks: (i) attacks on the switching mechanisms and (ii) false data injection attacks…

Event-triggered networked control of a linear dynamical system is investigated. Specifically, the dynamical system and the controller are assumed to be connected through a communication channel. State and control input information packets…

The rapid expansion of the Internet of Things (IoT) is reshaping communication and operational practices across industries, but it also broadens the attack surface and increases susceptibility to security breaches. Artificial Intelligence…

In this paper, we propose an AC power flow based cascading failure model that explicitly considers external weather conditions, extreme temperatures in particular, and evaluates the impact of extreme temperature on the initiation and…

In a power distribution network with energy storage systems (ESS) and advanced controls, traditional monitoring and protection schemes are not well suited for detecting anomalies such as malfunction of controllable devices. In this work, we…

While machine learning has significantly advanced Network Intrusion Detection Systems (NIDS), particularly within IoT environments where devices generate large volumes of data and are increasingly susceptible to cyber threats, these models…

The new wave of adversarial attacks that utilize gradient-related vulnerabilities in neural network-based classifiers makes Network Intrusion Detection Systems more open to such threats. Although state-of-the-art adversarial training…

Load redistribution (LR) attacks represent a practical and sophisticated form of false data injection (FDI) attacks, where the attacker manipulates grid data to influence economic operations of the grid through misleading security…

Internet of things (IoT) networks, boosted by 6G technology, are transforming various industries. However, their widespread adoption introduces significant security risks, particularly in detecting rare but potentially damaging…

Deployment of sensor network in hostile environment makes it mainly vulnerable to battery drainage attacks because it is impossible to recharge or replace the battery power of sensor nodes. Among different types of security threats, low…

This paper investigates the sparse recovery models for bad data detection and state estimation in power networks. Two sparse models, the sparse L1-relaxation model (L1-R) and the multi-stage convex relaxation model (Capped-L1), are compared…

This paper presents a novel learning based framework for predicting power outages caused by extreme events. The proposed approach targets low-probability high-consequence outage scenarios and leverages a comprehensive set of features…

The increasing integration of IoT-connected devices in smart grids has introduced new vulnerabilities at the distribution level. Of particular concern is the potential for cyberattacks that exploit high-wattage IoT devices, such as EV…

In modern power grids, a local failure or attack can trigger catastrophic cascading failures, which make it challenging to assess the attack vulnerability of power grids. In this Brief, we define the $K$-link attack problem and study the…

We consider the worst-case load-shedding problem in electric power networks where a number of transmission lines are to be taken out of service. The objective is to identify a pre-specified number of line outage that leads to the maximum…

This paper presents a real-time non-probabilistic detection mechanism to detect load-redistribution (LR) attacks against energy management systems (EMSs). Prior studies have shown that certain LR attacks can bypass conventional bad data…

Low Power Wide Area (LPWA) networks are making spectacular progress from design, standardisation, to commercialisation. At this time of fast-paced adoption, it is of utmost importance to analyse how well these technologies will scale as the…

In this paper, an artificial intelligence based grid hardening model is proposed with the objective of improving power grid resilience in response to extreme weather events. At first, a machine learning model is proposed to predict the…