| Title | An intrusion detection system integrating network-level intrusion detection and host-level intrusion detection |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | Liu, J., Xiao, K., Luo, L., Li, Y., Chen, L. |
| Conference Name | 2020 IEEE 20th International Conference on Software Quality, Reliability and Security (QRS) |
| Keywords | ADFA dataset, composability, Computer crime, computer network security, convolutional neural nets, cyber security, cyber-attackers, cyber-attacks, data mining, host-level IDS, host-level intrusion detection, IDS field, Intrusion detection, intrusion detection system, learning (artificial intelligence), machine learning, Metrics, network intrusion detection, network-level intrusion detection, Neural Network, NSL-KDD dataset, pubcrawl, resilience, Resiliency, Scalability, scalable neural-network-based hybrid IDS framework, security, software quality, software reliability |
| Abstract | With the rapid development of Internet, the issue of cyber security has increasingly gained more attention. An intrusion Detection System (IDS) is an effective technique to defend cyber-attacks and reduce security losses. However, the challenge of IDS lies in the diversity of cyber-attackers and the frequently-changing data requiring a flexible and efficient solution. To address this problem, machine learning approaches are being applied in the IDS field. In this paper, we propose an efficient scalable neural-network-based hybrid IDS framework with the combination of Host-level IDS (HIDS) and Network-level IDS (NIDS). We applied the autoencoders (AE) to NIDS and designed HIDS using word embedding and convolutional neural network. To evaluate the IDS, many experiments are performed on the public datasets NSL-KDD and ADFA. It can detect many attacks and reduce the security risk with high efficiency and excellent scalability. |
| DOI | 10.1109/QRS51102.2020.00028 |
| Citation Key | liu_intrusion_2020 |
An intrusion detection system integrating network-level intrusion detection and host-level intrusion detection