Zhang et al., 2025
ViewPDF| Publication | Publication Date | Title |
|---|---|---|
| RU2758041C2 (en) | Constant training for intrusion detection | |
| Miah et al. | Improving detection accuracy for imbalanced network intrusion classification using cluster-based under-sampling with random forests | |
| Weerasinghe et al. | Defending support vector machines against data poisoning attacks | |
| Zhang et al. | Continual learning with strategic selection and forgetting for network intrusion detection | |
| Raihan-Al-Masud et al. | Network intrusion detection system using voting ensemble machine learning | |
| Lefoane et al. | Multi-stage attack detection: Emerging challenges for wireless networks | |
| Rajora | Reviews research on applying machine learning techniques to reduce false positives for network intrusion detection systems | |
| Ahmed | Thwarting dos attacks: A framework for detection based on collective anomalies and clustering | |
| Ning et al. | Hibernated backdoor: A mutual information empowered backdoor attack to deep neural networks | |
| Lefoane et al. | Latent dirichlet allocation for the detection of multi-stage attacks | |
| Oikonomou et al. | A multi-class intrusion detection system based on continual learning | |
| Li et al. | Enhancing cybersecurity through fast machine learning algorithms | |
| Ahmed et al. | Enhancing Cloud Data Center Security through Deep Learning: A Comparative Analysis of RNN, CNN, and LSTM Models for Anomaly and Intrusion Detection | |
| Gowthami et al. | Zero-Day Threat Detection A Machine Learning Paradigm for Intrusion Prevention | |
| Chalichalamala et al. | An extreme gradient boost based classification and regression tree for network intrusion detection in IoT | |
| Cocoros et al. | Evaluating techniques for practical cloud-based network intrusion detection | |
| Pandya et al. | Machine Learning: Enhancing Cybersecurity through Attack Detection and Identification | |
| Flores et al. | Network anomaly detection by continuous hidden markov models: An evolutionary programming approach | |
| Nisya et al. | Implementation of Hyperparameter Tuning Random Forest Algorithm in Machine Learning for SDN Security: An Innovative Exploration of DDoS Attack Detection | |
| AH et al. | Adaptive memory replay for network intrusion detection: Tackling data drift and catastrophic forgetting | |
| Otokwala | Lightweight intrusion detection of attacks on the Internet of Things (IoT) in critical infrastructures | |
| Lee et al. | Network Intrusion Detection with Improved Feature Representation | |
| Kalaiselvi et al. | Hybrid Machine Learning Approach for Malware Analysis | |
| Katebi et al. | RAPSAMS: Robust affinity propagation clustering on static android malware stream | |
| Rajput et al. | Evaluation of machine learning based network attack detection |