A5023869783- Network Security and Intrusion Detection
- Internet Traffic Analysis and Secure E-voting
- Anomaly Detection Techniques and Applications
- Complex Network Analysis Techniques
- Data Visualization and Analytics
- Big Data Technologies and Applications
- Bioinformatics and Genomic Networks
- Advanced Computing and Algorithms
- Opinion Dynamics and Social Influence
- Image and Video Quality Assessment
- Advanced Malware Detection Techniques
Deakin University
2016-2021
Southwest University
2014
Cyber security has been thrust into the limelight in modern technological era because of an array attacks often bypassing untrained intrusion detection systems (IDSs). Therefore, greater attention directed on being able deciphering better methods for identifying attack types to train IDSs more effectively. Keycyber-attack insights exist big data; however, efficient approach is required determine strong become effective key areas. Despite rising growth IDS research, there a lack studies...
Summary With the large volume of network traffic flow, it is necessary to preprocess raw data before classification gain accurate results speedily. Feature selection an essential approach in preprocessing phase. The principal component analysis (PCA) recognized as effective and efficient method. In this paper, we classify flows by using PCA technique together with 6 machine learning algorithms—Naive Bayes, decision tree, 1‐nearest neighbor, random forest, support vector machine, H 2 O . We...
With the large volume of network traffic flow, it is necessary to preprocess raw data before classification gain accurate results speedily. Feature selection an essential approach in preprocessing phase. The Principal Component Analysis (PCA) recognized as effective and efficient method. In this paper, we classify by using PCA technique together with six machine learning algorithms - Naive Bayes, Decision Tree, 1-Nearest Neighbor (NN), Random Forest, Support Vector Machine (SVM) H2O. We...
Network traffic analytics technology is a cornerstone for cyber security systems. We demonstrate its use through three popular and contemporary applications in intrusion detection, malware analysis botnet detection. However, automated faces the challenges raised by big data. In terms of data's characteristics --- volume, variety velocity, we review state art techniques to mitigate key including real-time classification, unknown efficiency classifiers. The new using statistical features,...
Microwave links are widely employed in cellular data networks due to high-speed Internet access and easy installation, thus reducing network implementation costs. However, these prone failure may lead performance degradation, unavailability service disruption. Early detection of any link failures is critical maintain quality, but the complex environment dynamic nature information makes this a complicated process. In work, we propose Long Short-Term Memory (LSTM)-based feature fusion...