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04/07/2023
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 sy...
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03/28/2023
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, int...
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09/29/2022
A Secure Federated Learning Framework for Residential Short Term Load Forecasting
Smart meter measurements, though critical for accurate demand forecastin...
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09/08/2022
A Survey of Recent Advances in Deep Learning Models for Detecting Malware in Desktop and Mobile Platforms
Malware is one of the most common and severe cyber-attack today. Malware...
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09/08/2022
MalDetConv: Automated Behaviour-based Malware Detection Framework Based on Natural Language Processing and Deep Learning Techniques
The popularity of Windows attracts the attention of hackers/cyber-attack...
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03/01/2022
FedREP: Towards Horizontal Federated Load Forecasting for Retail Energy Providers
As Smart Meters are collecting and transmitting household energy consump...
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11/28/2021
False Data Injection Threats in Active Distribution Systems: A Comprehensive Survey
With the proliferation of smart devices and revolutions in communication...
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03/30/2021
A Taxonomy of Cyber Defence Strategies Against False Data Attacks in Smart Grid
Modern electric power grid, known as the Smart Grid, has fast transforme...
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08/21/2014