A5100342505- Network Security and Intrusion Detection
- Anomaly Detection Techniques and Applications
- Advanced Malware Detection Techniques
- Fire Detection and Safety Systems
- Internet Traffic Analysis and Secure E-voting
- Advanced Algorithms and Applications
- Fire dynamics and safety research
- Face and Expression Recognition
- Evacuation and Crowd Dynamics
- Video Surveillance and Tracking Methods
- Advanced Computational Techniques and Applications
Anhui University of Science and Technology
2023-2024
The increasing prevalence of unknown-type attacks on the Internet highlights importance developing efficient intrusion detection systems. While machine learning-based techniques can detect unknown types attacks, need for innovative approaches becomes evident, as traditional methods may not be sufficient. In this research, we propose a deep solution called log-cosh variational autoencoder (LVAE) to address challenge. LVAE inherits strong modeling abilities (VAE), enabling it understand...
A large amount of sensitive information is generated in today’s evolving network environment. Some hackers utilize low-frequency attacks to steal from users. This generates minority attack samples real traffic. As a result, the data distribution traffic asymmetric, with number normal and rare To address imbalance problem, intrusion detection systems mainly rely on machine-learning-based methods detect attacks. Although this approach can attacks, performance not satisfactory. solve...
The rising number of unknown-type attacks on the Internet emphasizes significance developing efficient intrusion detection systems, even if machine learning-based techniques can detect unknown types attacks. necessity for innovative is highlighted by possibility that traditional learning will not be sufficient identifying these In this research, we address difficulty proposing a deep solution: log-cosh variational autoencoder (LVAE). When it comes to understanding intricate data...