Related papers: Vulnerability Analysis and Consequences of False D…
This letter proposes a novel, fully distributed, transient-safe resilient secondary control strategies for AC microgrids, addressing unbounded false data injection (FDI) attacks on control input channels. Unlike existing methods that focus…
Although adverse effects of attacks have been acknowledged in many cyber-physical systems, there is no system-theoretic comprehension of how a compromised agent can leverage communication capabilities to maximize the damage in distributed…
Contingency Analysis (CA) is a core component of the Energy Management System (EMS) in the power grid. The goal of CA is to operate the power system in a secure manner by analyzing the system subject to a contingency (e.g., the outage of a…
Data attacks on state estimation modify part of system measurements such that the tempered measurements cause incorrect system state estimates. Attack techniques proposed in the literature often require detailed knowledge of system…
In this paper, we present a novel distributed state estimation approach in networked DC microgrids to detect the false data injection in the microgrid control network. Each microgrid monitored by a distributed state estimator will detect if…
Network-based attacks on control systems may alter sensor data delivered to the controller, effectively causing degradation in control performance. As a result, having access to accurate state estimates, even in the presence of attacks on…
This paper addresses the problem of output consensus in linear passive multi-agent systems under a False Data Injection (FDI) attack, considering the unavailability of complete state information. Our formulation relies on an event-based…
Fault Injection is the study of observing how systems behave under unusual stress, environmental or otherwise. In practice, fault injection involves testing the limits of computer systems and finding novel ways to potentially break…
The increase in network connectivity has also resulted in several high-profile attacks on cyber-physical systems. An attacker that manages to access a local network could remotely affect control performance by tampering with sensor…
New methods that exploit sparse structures arising in smart grid networks are proposed for the state estimation problem when data injection attacks are present. First, construction strategies for unobservable sparse data injection attacks…
Cyber-physical systems can be subject to sensor attacks, e.g., sensor spoofing, leading to unsafe behaviors. This paper addresses this problem in the context of linear systems when an omniscient attacker can spoof several system sensors at…
With the increasing integration of cyber-physical systems (CPS) into critical applications, ensuring their resilience against cyberattacks is paramount. A particularly concerning threat is the vulnerability of CPS to deceptive attacks that…
In this work, we focus on analyzing vulnerability of nonlinear dynamical control systems to stealthy false data injection attacks on sensors. We start by defining the stealthiness notion in the most general form where an attack is…
This paper considers the problem of detector tuning against false data injection attacks. In particular, we consider an adversary injecting false sensor data to maximize the state deviation of the plant, referred to as impact, whilst being…
This paper presents a hybrid data-driven physics model-based framework for real time monitoring in smart grids. As the power grid transitions to the use of smart grid technology, it's real time monitoring becomes more vulnerable to cyber…
We study the security threats of power system operation brought by a class of data injection attacks upon load forecasting algorithms. In particular, with minimal assumptions on the knowledge and ability of the attacker, we design attack…
Electric power grids are evolving towards intellectualization such as Smart Grids or active-adaptive networks. Intelligent power network implies usage of sensors, smart meters, electronic devices and sophisticated communication network.…
This paper presents a novel data-driven framework to aid in system state estimation when the power system is under unobservable false data injection attacks. The proposed framework dynamically detects and classifies false data injection…
This paper assesses the resilience of IEC 61850 digital substations under False Data Injection Attacks (FDIAs) targeting the Sampled Values (SV) protocol. The multicast nature of SV, while enabling time-critical automation, exposes…
False Data Injection (FDI) attacks are a common form of Cyber-attack targetting smart grids. Detection of stealthy FDI attacks is impossible by the current bad data detection systems. Machine learning is one of the alternative methods…