Mohamed I. Ibrahem

Orcid: 0000-0002-8000-4161

According to our database1, Mohamed I. Ibrahem authored at least 31 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Advanced 3D Face Reconstruction from Single 2D Images Using Enhanced Adversarial Neural Networks and Graph Neural Networks.
Sensors, October, 2024

A Lightweight Privacy-Preserving Load Forecasting and Monitoring Scheme Supporting Dynamic Billing for Smart Grids: No KDC Required.
IEEE Internet Things J., October, 2024

Securing Smart Grid False Data Detectors Against White-Box Evasion Attacks Without Sacrificing Accuracy.
IEEE Internet Things J., October, 2024

The Potential of Deep Learning in Underwater Wireless Sensor Networks and Noise Canceling for the Effective Monitoring of Aquatic Life.
Sensors, September, 2024

Deep Complex Gated Recurrent Networks-Based IoT Network Intrusion Detection Systems.
Sensors, September, 2024

Securing Smart Grids: Deep Reinforcement Learning Approach for Detecting Cyber-Attacks.
Proceedings of the International Conference on Smart Applications, 2024

Enhancing Diabetes Prediction Based on Pair-Wise Ensemble Learning Model Selection.
Proceedings of the International Conference on Smart Applications, 2024

Poisoning Attack Mitigation for Privacy-Preserving Federated Learning-Based Energy Theft Detection.
Proceedings of the IEEE International Conference on Communications, 2024

Privacy-preserving, Lightweight, and Decentralized Load Forecasting in Smart Grid AMI Networks.
Proceedings of the IEEE International Conference on Communications, 2024

Federated Learning With Selective Knowledge Distillation Over Bandwidth-constrained Wireless Networks.
Proceedings of the IEEE International Conference on Communications, 2024

FedSafe-No KDC Needed: Decentralized Federated Learning with Enhanced Security and Efficiency.
Proceedings of the 21st IEEE Consumer Communications & Networking Conference, 2024

2023
Real-Time Anomaly Detection for Water Quality Sensor Monitoring Based on Multivariate Deep Learning Technique.
Sensors, October, 2023

Enhancing Security in ZigBee Wireless Sensor Networks: A New Approach and Mutual Authentication Scheme for D2D Communication.
Sensors, 2023

Privacy-Preserving and Communication-Efficient Energy Prediction Scheme Based on Federated Learning for Smart Grids.
IEEE Internet Things J., 2023

Detection of Distributed Denial of Charge (DDoC) Attacks Using Deep Neural Networks With Vector Embedding.
IEEE Access, 2023

Privacy-Preserving Detection of Power Theft in Smart Grid Change and Transmit (CAT) Advanced Metering Infrastructure.
IEEE Access, 2023

Joint Knowledge Distillation and Local Differential Privacy for Communication-Efficient Federated Learning in Heterogeneous Systems.
Proceedings of the IEEE Global Communications Conference, 2023

Secure and Efficient Federated Learning in LEO Constellations Using Decentralized Key Generation and On-Orbit Model Aggregation.
Proceedings of the IEEE Global Communications Conference, 2023

Moreau Envelopes-Based Personalized Asynchronous Federated Learning: Improving Practicality in Network Edge Intelligence.
Proceedings of the IEEE Global Communications Conference, 2023

2022
Electricity-Theft Detection for Change-and-Transmit Advanced Metering Infrastructure.
IEEE Internet Things J., 2022

Detection of False-Reading Attacks in Smart Grid Net-Metering System.
IEEE Internet Things J., 2022

Real-Time Detection of False Readings in Smart Grid AMI Using Deep and Ensemble Learning.
IEEE Access, 2022

Privacy-preserving and Efficient Decentralized Federated Learning-based Energy Theft Detector.
Proceedings of the IEEE Global Communications Conference, 2022

2021
Efficient Privacy-Preserving Electricity Theft Detection With Dynamic Billing and Load Monitoring for AMI Networks.
IEEE Internet Things J., 2021

Privacy Preserving and Efficient Data Collection Scheme for AMI Networks Using Deep Learning.
IEEE Internet Things J., 2021

Countering Presence Privacy Attack in Efficient AMI Networks Using Interactive Deep-Learning.
Proceedings of the International Symposium on Networks, Computers and Communications, 2021

Detecting Electricity Theft Cyber-attacks in CAT AMI System Using Machine Learning.
Proceedings of the International Symposium on Networks, Computers and Communications, 2021

Detecting Electricity Fraud in the Net-Metering System Using Deep Learning.
Proceedings of the International Symposium on Networks, Computers and Communications, 2021

UBLS: User-Based Location Selection Scheme for Preserving Location Privacy.
Proceedings of the IEEE International Conference on Communications Workshops, 2021

2020
Detection of False-Reading Attacks in the AMI Net-Metering System.
CoRR, 2020

PMBFE: Efficient and Privacy-Preserving Monitoring and Billing Using Functional Encryption for AMI Networks.
Proceedings of the 2020 International Symposium on Networks, Computers and Communications, 2020


  Loading...