False data injection attack in smart grid cyber physical system: Issues, challenges, and future direction
Smart grid integrates the physical power system infrastructure with internet-of-things-based
digital communication networks that work together for grid stability, sustainability, and …
digital communication networks that work together for grid stability, sustainability, and …
An Overview of Supervised Machine Learning Approaches for Applications in Active Distribution Networks
Distribution grids must be regularly updated to meet the global electricity demand. Some of
these updates result in fundamental changes to the structure of the grid network. Some …
these updates result in fundamental changes to the structure of the grid network. Some …
On protection schemes for ac microgrids: challenges and opportunities
JID Cisneros-Saldana, S Samal… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
The integration of Distributed energy resources (DERs) into distribution networks has been
increasing in recent years, causing concerns related to operation, control, stability, reliability …
increasing in recent years, causing concerns related to operation, control, stability, reliability …
A secure federated learning framework for residential short term load forecasting
Smart meter measurements, though critical for accurate demand forecasting, face several
drawbacks including consumers' privacy, data breach issues, to name a few. Recent …
drawbacks including consumers' privacy, data breach issues, to name a few. Recent …
Deep learning hybridization for improved malware detection in smart Internet of Things
AA Almazroi, N Ayub - Scientific Reports, 2024 - nature.com
The rapid expansion of AI-enabled Internet of Things (IoT) devices presents significant
security challenges, impacting both privacy and organizational resources. The dynamic …
security challenges, impacting both privacy and organizational resources. The dynamic …
Synthetic energy data generation using time variant generative adversarial network
S Asre, A Anwar - Electronics, 2022 - mdpi.com
Energy consumption data is being used for improving the energy efficiency and minimizing
the cost. However, obtaining energy consumption data has two major challenges:(i) data …
the cost. However, obtaining energy consumption data has two major challenges:(i) data …
[HTML][HTML] FedDiSC: A computation-efficient federated learning framework for power systems disturbance and cyber attack discrimination
With the growing concern about the security and privacy of smart grid systems, cyberattacks
on critical power grid components, such as state estimation, have proven to be one of the top …
on critical power grid components, such as state estimation, have proven to be one of the top …
Fedrep: Towards horizontal federated load forecasting for retail energy providers
As Smart Meters are collecting and transmitting household energy consumption data to
Retail Energy Providers (REP), the main challenge is to ensure the effective use of fine …
Retail Energy Providers (REP), the main challenge is to ensure the effective use of fine …
Fedisa: A semi-asynchronous federated learning framework for power system fault and cyberattack discrimination
With growing security and privacy concerns in the Smart Grid domain, intrusion detection on
critical energy infrastructure has become a high priority in recent years. To remedy the …
critical energy infrastructure has become a high priority in recent years. To remedy the …
False data injection attacks in smart grids: State of the art and way forward
M Irfan, A Sadighian, A Tanveer, SJ Al-Naimi… - arXiv preprint arXiv …, 2023 - arxiv.org
In the recent years cyberattacks to smart grids are becoming more frequent Among the many
malicious activities that can be launched against smart grids False Data Injection FDI attacks …
malicious activities that can be launched against smart grids False Data Injection FDI attacks …