Ehsan Hallaji

CoRR, February, 2025

FedNIA: Noise-Induced Activation Analysis for Mitigating Data Poisoning in FL.

[BibT_eX]

[DOI]

CoRR, February, 2025

A Study on the Importance of Features in Detecting Advanced Persistent Threats Using Machine Learning.

[BibT_eX]

[DOI]

CoRR, February, 2025

Federated continual learning: Concepts, challenges, and solutions.

[BibT_eX]

[DOI]

Parisa Hamedi

Neurocomputing, 2025

Enhancing Cyberspace Security with Phishing Detection and Defense Using Machine Learning Models.

[BibT_eX]

[DOI]

MD Nazmul Haque Siam

Proceedings of the 13th International Symposium on Digital Forensics and Security, 2025

2024

IEEE 118-Bus Cyber-Physical Power System Data Streams.

[BibT_eX]

[DOI]

Dataset, November, 2024

Decentralized Federated Learning: A Survey on Security and Privacy.

[BibT_eX]

[DOI]

IEEE Trans. Big Data, April, 2024

Expanding analytical capabilities in intrusion detection through ensemble-based multi-label classification.

[BibT_eX]

[DOI]

Comput. Secur., 2024

Bio-Inspired Intelligent Anomaly Diagnosis System for Health Monitoring in Connected Vehicles.

[BibT_eX]

[DOI]

Mahsa Jalali

Proceedings of the IEEE International Conference on Smart Mobility, 2024

2023

Label noise analysis meets adversarial training: A defense against label poisoning in federated learning.

[BibT_eX]

[DOI]

Enrique Herrera-Viedma

Knowl. Based Syst., April, 2023

Constrained Generative Adversarial Learning for Dimensionality Reduction.

[BibT_eX]

[DOI]

Vasile Palade

IEEE Trans. Knowl. Data Eng., March, 2023

Learning From High-Dimensional Cyber-Physical Data Streams for Diagnosing Faults in Smart Grids.

[BibT_eX]

[DOI]

CoRR, 2023

2022

A Stream Learning Approach for Real-Time Identification of False Data Injection Attacks in Cyber-Physical Power Systems.

[BibT_eX]

[DOI]

IEEE Trans. Inf. Forensics Secur., 2022

Generative-Adversarial Class-Imbalance Learning for Classifying Cyber-Attacks and Faults - A Cyber-Physical Power System.

[BibT_eX]

[DOI]

IEEE Trans. Dependable Secur. Comput., 2022

DLIN: Deep Ladder Imputation Network.

[BibT_eX]

[DOI]

IEEE Trans. Cybern., 2022

Federated and Transfer Learning: A Survey on Adversaries and Defense Mechanisms.

[BibT_eX]

[DOI]

CoRR, 2022

2021

Adversarial Semi-Supervised Learning for Diagnosing Faults and Attacks in Power Grids.

[BibT_eX]

[DOI]

IEEE Trans. Smart Grid, 2021

Generative adversarial dimensionality reduction for diagnosing faults and attacks in cyber-physical systems.

[BibT_eX]

[DOI]

Neurocomputing, 2021

Unsupervised concrete feature selection based on mutual information for diagnosing faults and cyber-attacks in power systems.

[BibT_eX]

[DOI]

Eng. Appl. Artif. Intell., 2021

Adversarial Learning on Incomplete and Imbalanced Medical Data for Robust Survival Prediction of Liver Transplant Patients.

[BibT_eX]

[DOI]

IEEE Access, 2021

A Critical Study on the Impact of Missing Data Imputation for Classifying Intrusions in Cyber-Physical Water Systems.

[BibT_eX]

[DOI]

Ranim Aljoudi

Proceedings of the IECON 2021, 2021

2020

Detection of Malicious SCADA Communications via Multi-Subspace Feature Selection.

[BibT_eX]

[DOI]

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

2019

A Semi-Supervised Diagnostic Framework Based on the Surface Estimation of Faulty Distributions.

[BibT_eX]

[DOI]

IEEE Trans. Ind. Informatics, 2019

A Novelty Detector and Extreme Verification Latency Model for Nonstationary Environments.

[BibT_eX]

[DOI]

IEEE Trans. Ind. Electron., 2019

Information Fusion and Semi-Supervised Deep Learning Scheme for Diagnosing Gear Faults in Induction Machine Systems.

[BibT_eX]

[DOI]