Mohsen Eslamnejad

Mohsen Eslamnejad is a Research Fellow at the 5G/6G Innovation Centre (5G/6GIC), Institute for Communication Systems (ICS) at the University of Surrey, UK. He received an MSc degree in Cyber Security from the University of Portsmouth, UK, where he also was a Research Associate in the School of Computing. His research interests include AI, machine learning applications in cybersecurity, federated learning, split learning, and adversarial machine learning.

Mohsen has extensive experience in programming and leading professional teams. As the programming team lead at ASPA, he supports team members with programming tasks by solving challenges, fixing errors, and introducing new methods in machine learning using Python. In this role, he has contributed to several projects at ASPA, including the following:

• SPLIT-IDS: Label Flipping Attack against Split Learning based Intrusion Detection System

• Secure Electric Traction Drives Using Federated Predictor in Connected Vehicles

• Uncertainty-aware Deep Botnet Detection System in Presence of Perturbed Sample

• Enhancing Robustness of Federated Learning against Label Flipping Attacks through Data Augmentation based Defenses

• Unveiling vulnerabilities in deep learning-based malware detection: Differential privacy driven adversarial attacks.

• Federated Learning Under Attack: Exposing Vulnerabilities through Data Poisoning Attacks in Computer Networks

• Verifying the Robustness of Machine Learning based Intrusion Detection Against Adversarial Perturbation

• Moving Towards Explainable Artificial Intelligence Using Fuzzy Rule-Based Networks in Decision-Making Process.

• Model poisoning attack against federated learning with adaptive aggregation

• Adversarial Deep Botnet Detection: Uncertainty Aware Approaches