Khan, 2009
| Publication | Publication Date | Title |
|---|---|---|
| US10938845B2 (en) | Detection of user behavior deviation from defined user groups | |
| Boukhtouta et al. | Network malware classification comparison using DPI and flow packet headers | |
| Catak et al. | Distributed denial of service attack detection using autoencoder and deep neural networks | |
| Gogoi et al. | MLH-IDS: a multi-level hybrid intrusion detection method | |
| US7690037B1 (en) | Filtering training data for machine learning | |
| US8682812B1 (en) | Machine learning based botnet detection using real-time extracted traffic features | |
| Tahseen et al. | Extraction for Big Data Cyber Security Analytics | |
| Sharma et al. | An improved network intrusion detection technique based on k-means clustering via Naïve bayes classification | |
| Min | An analysis of K-means algorithm based network intrusion detection system | |
| CN109344913B (en) | Network intrusion behavior detection method based on improved MajorCluster clustering | |
| Yehezkel et al. | Network anomaly detection using transfer learning based on auto-encoders loss normalization | |
| US11140123B2 (en) | Community detection based on DNS querying patterns | |
| US20250063064A1 (en) | Detecting Malicious Email Campaigns with Unique but Similarly-Spelled Attachments | |
| Fallahi et al. | Automated flow-based rule generation for network intrusion detection systems | |
| Kozik et al. | Cost‐Sensitive Distributed Machine Learning for NetFlow‐Based Botnet Activity Detection | |
| Niandong et al. | Detection of probe flow anomalies using information entropy and random forest method | |
| Choi et al. | An easy-to-use framework to build and operate ai-based intrusion detection for in-situ monitoring | |
| Zwane et al. | Ensemble learning approach for flow-based intrusion detection system | |
| Liu et al. | Doc2vec-based insider threat detection through behaviour analysis of multi-source security logs | |
| Rajeswari et al. | An active rule approach for network intrusion detection with enhanced C4. 5 algorithm | |
| Rejimol Robinson et al. | Improved minority attack detection in Intrusion Detection System using efficient feature selection algorithms | |
| Hubballi et al. | Layered higher order n-grams for hardening payload based anomaly intrusion detection | |
| Ji et al. | Feature driven learning framework for cybersecurity event detection | |
| Komisarek et al. | A novel, refined dataset for real-time Network Intrusion Detection | |
| Sabri et al. | Hybrid of rough set theory and artificial immune recognition system as a solution to decrease false alarm rate in intrusion detection system |