Related papers: Data Framing Attack on State Estimation
This paper considers the state reconstruction problem for discrete-time cyber-physical systems when some of the sensors can be arbitrarily corrupted by malicious attacks where the attacked sensors belong to an unknown set. We first prove…
Recent research has shown that the security of power grids can be seriously threatened by botnet-type cyber attacks that target a large number of high-wattage smart electrical appliances owned by end-users. Accurate detection and…
The smart grid combines the classical power system with information technology, leading to a cyber-physical system. In such an environment the malicious injection of data has the potential to cause severe consequences. Classical…
Load forecasting plays a critical role in the operation and planning of power systems. By using input features such as historical loads and weather forecasts, system operators and utilities build forecast models to guide decision making in…
In this paper, we consider the problem of state estimation through observations possibly corrupted with both bad data and additive observation noises. A mixed $\ell_1$ and $\ell_2$ convex programming is used to separate both sparse bad data…
This paper studies the performance and resilience of a linear cyber-physical control system (CPCS) with attack detection and reactive attack mitigation in the context of power grids. It addresses the problem of deriving an optimal sequence…
The resilience of Supervisory Control and Data Acquisition (SCADA) systems for electric power networks for certain cyber-attacks is considered. We analyze the vulnerability of the measurement system to false data attack on communicated…
This article introduces an anomaly detection based algorithm (AD-CPS) to detect false data injection attacks that fall under the category of data deception/integrity attacks, but with arbitrary information structure, in cyber-physical…
Power network and generators state estimation are usually tackled as separate problems. We propose a dynamic scheme for the simultaneous estimation of the network and the generator states. The estimation is formulated as an optimization…
Machine-learning models can be fooled by adversarial examples, i.e., carefully-crafted input perturbations that force models to output wrong predictions. While uncertainty quantification has been recently proposed to detect adversarial…
In a sensor network, some sensors usually provide the same or equivalent measurement information, which is not taken into account by the existing secure state estimation methods against sparse sensor attacks such that the computational…
In this paper, we examine a variety of strategies for numerical quantum-state estimation from data of the sort commonly measured in experiments involving quantum state tomography. We find that, in some important circumstances, an elaborate…
Malicious attacks in the power system can eventually result in a large-scale cascade failure if not attended on time. These attacks, which are traditionally classified into \emph{physical} and \emph{cyber attacks}, can be avoided by using…
We propose a new defense mechanism against undetected infiltration into controllers in cyber-physical systems. To this end, we cautiously design the outputs of the sensors that monitor the state of the system. Different from the defense…
In many applications with real-world consequences, it is crucial to develop reliable uncertainty estimation for the predictions made by the AI decision systems. Targeting at the goal of estimating uncertainty, various deep neural network…
Smart Grid (SG) research and development has drawn much attention from academia, industry and government due to the great impact it will have on society, economics and the environment. Securing the SG is a considerably significant challenge…
The reported work points at developing a practical approach for power transmission planners to secure power networks from potential deliberate attacks. We study the interaction between a system planner (defender) and a rational attacker who…
The estimation of signal parameters using quantized data is a recurrent problem in electrical engineering. As an example, this includes the estimation of a noisy constant value and of the parameters of a sinewave, that is, its amplitude,…
We consider time synchronization attack against multi-system scheduling in a remote state estimation scenario where a number of sensors monitor different linear dynamical processes and schedule their transmissions through a shared collision…
Quantum key distribution (QKD) protocol has been proved to provide unconditionally secure key between two remote legitimate users in theory. Key distribution signals are transmitted in a quantum channel which is established by the…