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2025
A Two-Stage Hybrid Federated Learning Framework for Privacy-Preserving IoT Anomaly Detection and Classification
IoT
2025
The good, the bad, and the algorithm: The impact of generative AI on cybersecurity
Neurocomputing
2024
Twenty-two years since revealing cross-site scripting attacks: A systematic mapping and a comprehensive survey
Computer Science Review
2024
An ensemble learning framework for the detection of RPL attacks in IoT networks based on the genetic feature selection approach
Ad Hoc Networks
2024
AI capabilities in cybersecurity: detection, prevention and response to SQL injections, XSS, and CSRF attacks
Mathematical structures and modeling
2024
GUIDE: GAN-based UAV IDS Enhancement
Computers & Security
2023
Dynamic feature selection model for adaptive cross site scripting attack detection using developed multi-agent deep Q learning model
Journal of King Saud University - Computer and Information Sciences
2023
Anomaly-Based Intrusion on IoT Networks Using AIGAN-a Generative Adversarial Network
IEEE Access
2023
2023 3rd International Conference on Computing and Information Technology (ICCIT)
2023
Analysis of Methods and Means for Ensuring Cybersecurity of Web Services Using Artificial Intelligence
Èlektronnoe modelirovanie
2023
Machine and Deep Learning-based XSS Detection Approaches: A Systematic Literature Review
Journal of King Saud University - Computer and Information Sciences
2023
A Survey of Internet of Things and Cyber-Physical Systems: Standards, Algorithms, Applications, Security, Challenges, and Future Directions
Information
2022
2022 17th Asia Joint Conference on Information Security (AsiaJCIS)
2022
MNN-XSS: Modular Neural Network Based Approach for XSS Attack Detection
Computers, Materials & Continua
2021
Communications in Computer and Information Science
2021
ML-LGBM: A Machine Learning Model Based on Light Gradient Boosting Machine for the Detection of Version Number Attacks in RPL-Based Networks
IEEE Access
2021
Selecting the Suitable Resampling Strategy for Imbalanced Data Classification Regarding Dataset Properties. An Approach Based on Association Models
Applied Sciences