43 citations · 50 across the 4 of their papers we have counts for
5 papers
FedDiSC: A Computation-efficient Federated Learning Framework for Power Systems Disturbance and Cyber Attack Discrimination
Muhammad Akbar Husnoo, Adnan Anwar, Haftu Tasew Reda +4
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 th…
FeDiSa: A Semi-asynchronous Federated Learning Framework for Power System Fault and Cyberattack Discrimination
Muhammad Akbar Husnoo, Adnan Anwar, Haftu Tasew Reda +4
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…
A Secure Federated Learning Framework for Residential Short Term Load Forecasting
Muhammad Akbar Husnoo, Adnan Anwar, Nasser Hosseinzadeh +3
Smart meter measurements, though critical for accurate demand forecasting, face several drawbacks including consumers' privacy, data breach issues, to name a few. Recent literature…
FedREP: Towards Horizontal Federated Load Forecasting for Retail Energy Providers
Muhammad Akbar Husnoo, Adnan Anwar, Nasser Hosseinzadeh +3
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-graine…
False Data Injection Threats in Active Distribution Systems: A Comprehensive Survey
Muhammad Akbar Husnoo, Adnan Anwar, Nasser Hosseinzadeh +3
With the proliferation of smart devices and revolutions in communications, electrical distribution systems are gradually shifting from passive, manually-operated and inflexible one…