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Found 10 papers, 1 papers with code
Anomaly Detection in Power Markets and Systems
The widespread use of information and communication technology (ICT) over the course of the last decades has been a primary catalyst behind the digitalization of power systems.
Mitigating Attacks on Artificial Intelligence-based Spectrum Sensing for Cellular Network Signals
Cellular networks (LTE, 5G, and beyond) are dramatically growing with high demand from consumers and more promising than the other wireless networks with advanced telecommunication technologies.
Hybrid AI-based Anomaly Detection Model using Phasor Measurement Unit Data
Over the last few decades, extensive use of information and communication technologies has been the main driver of the digitalization of power systems.
Defensive Distillation based Adversarial Attacks Mitigation Method for Channel Estimation using Deep Learning Models in Next-Generation Wireless Networks
The key motivation of NextG networks is to meet the high demand for those applications by improving and optimizing network functions.
Homomorphic Encryption and Federated Learning based Privacy-Preserving CNN Training: COVID-19 Detection Use-Case
In this study, the proposed algorithm using a real-world medical dataset is evaluated in terms of the model performance.
The Adversarial Security Mitigations of mmWave Beamforming Prediction Models using Defensive Distillation and Adversarial Retraining
This paper presents the security vulnerabilities in deep learning for beamforming prediction using deep neural networks (DNNs) in 6G wireless networks, which treats the beamforming prediction as a multi-output regression problem.
LCOE-based Pricing for DLT-enabled Local Energy Trading Platforms
In this paper, a new pricing mechanism based on the Levelized Cost of Electricity is proposed, with the intention of securing profitability for the prosumers, as well as creating a transparent and fair price for all market participants.
Security Concerns on Machine Learning Solutions for 6G Networks in mmWave Beam Prediction
We also present the adversarial learning mitigation method's performance for 6G security in mmWave beam prediction application with fast gradient sign method attack.
Probabilistic Solar Power Forecasting: Long Short-Term Memory Network vs Simpler Approaches
Currently, there is a trend towards the use of deep learning probabilistic forecasting methods.
Internet of Predictable Things (IoPT) Framework to Increase Cyber-Physical System Resiliency
During the last two decades, distributed energy systems, especially renewable energy sources (RES), have become more economically viable with increasing market share and penetration levels on power systems.
