Priyanka Verma
Orcid: 0000-0002-2153-893XAffiliations:
- University of Limerick, Department of Electronics and Computer Engineering, Castletroy, Limerick, Ireland
- University of Galway, Data Science Institute, Ireland
According to our database1,
Priyanka Verma
authored at least 24 papers
between 2020 and 2025.
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Bibliography
2025
A Combined Supervised and Unsupervised Deep Learning Approach for Intrusion Detection in IoT Traffic in an Edge Computing Environment.
SN Comput. Sci., August, 2025
ABIDS-VEM: leveraging an equilibrium optimizer and data ramification in association with ensemble learning for anomaly-based intrusion detection system.
J. Supercomput., May, 2025
Leveraging Transfer Learning Domain Adaptation Model With Federated Learning to Revolutionise Healthcare.
Expert Syst. J. Knowl. Eng., February, 2025
Blockchain-Based Model for Secure and Fair Data Provision in Crowdsourced Drone Services.
IEEE Open J. Commun. Soc., 2025
Toward a Unified Understanding of Cyber Resilience: Concepts, Strategies, and Future Directions.
IEEE Access, 2025
PPFL-DCS: Privacy-Preserving Federated Learning Using Neural Transformer and Leveraging Dynamic Client Selection to Accommodate Data Diversity.
IEEE Access, 2025
2024
PULSE: Proactive uncovering of latent severe anomalous events in IIoT using LSTM-RF model.
Clust. Comput., December, 2024
Multim. Tools Appl., November, 2024
A Stacked Ensemble Approach to Generalize the Classifier Prediction for the Detection of DDoS Attack in Cloud Network.
Mob. Networks Appl., October, 2024
A federated learning approach to network intrusion detection using residual networks in industrial IoT networks.
J. Supercomput., September, 2024
Uncovering collateral damages and advanced defense strategies in cloud environments against DDoS attacks: A comprehensive review.
Trans. Emerg. Telecommun. Technol., April, 2024
Leveraging Gametic Heredity in Oversampling Techniques to Handle Class Imbalance for Efficient Cyberthreat Detection in IIoT.
IEEE Trans. Consumer Electron., February, 2024
Zero-Day Guardian: A Dual Model Enabled Federated Learning Framework for Handling Zero-Day Attacks in 5G Enabled IIoT.
IEEE Trans. Consumer Electron., February, 2024
Revolutionizing Human Activity Recognition in Healthcare: Harnessing Red Deer for Feature Selection and Focal Loss-Based MLP for Classification.
Proceedings of the International Conference on Software, 2024
2023
Out-of-Distribution Data Generation for Fault Detection and Diagnosis in Industrial Systems.
IEEE Access, 2023
FedTIU: Securing Virtualized PLCs Against DDoS Attacks Using a Federated Learning Enabled Threat Intelligence Unit.
Proceedings of the 2023 IEEE International Conference on Smart Computing, 2023
Improving Product Quality Control in Smart Manufacturing through Transfer Learning-Based Fault Detection.
Proceedings of the 2023 IEEE International Conference on Smart Computing, 2023
DQ-DeepLearn: Data Quality Driven Deep Learning Approach for Enhanced Predictive Maintenance in Smart Manufacturing.
Proceedings of the 5th International Conference on Industry 4.0 and Smart Manufacturing (ISM 2023), 2023
PerCFed: An Effective Personalized Clustered Federated Learning Mechanism to Handle non-IID Challenges for Industry 4.0.
Proceedings of the 12th IEEE International Conference on Cloud Networking, 2023
2022
FLDID: Federated Learning Enabled Deep Intrusion Detection in Smart Manufacturing Industries.
Sensors, 2022
2021
A service governance and isolation based approach to mitigate internal collateral damages in cloud caused by DDoS attack.
Wirel. Networks, 2021
An Impact Analysis and Detection of HTTP Flooding Attack in Cloud Using Bio-Inspired Clustering Approach.
Int. J. Swarm Intell. Res., 2021
A request aware module using CS-IDR to reduce VM level collateral damages caused by DDoS attack in cloud environment.
Clust. Comput., 2021
2020
Wirel. Pers. Commun., 2020