T Kim, W Pak - IEEE Access, 2022 - ieeexplore.ieee.org
Network Intrusion Detection Systems (NIDSs) using pattern matching have a fatal weakness in that they cannot detect new attacks because they only learn existing patterns and use …
Machine learning (ML)-based network intrusion detection systems (NIDSs) depend entirely on the performance of machine learning models. Therefore, many studies have been …
T Kim, W Pak - Future Generation Computer Systems, 2022 - Elsevier
The network intrusion detection system needs to detect intrusions in real-time without delay when an intrusion is attempted. To this end, various approaches, such as packet-based …
X Han, S Cui, S Liu, C Zhang, B Jiang, Z Lu - Computers & Security, 2023 - Elsevier
Network intrusion detection system plays a critical role in protecting the target network from attacks. However, most existing detection methods cannot fully utilize the information …
Current intrusion detection techniques cannot keep up with the increasing amount and complexity of cyber attacks. In fact, most of the traffic is encrypted and does not allow to …
Current flow-based Network Intrusion Detection Systems (NIDSs) have the drawback of detecting attacks only once the flow has ended, resulting in potential delays in attack …
Network intrusion detection systems (NIDS) today must quickly provide visibility into anomalous behavior on a growing amount of data. Meanwhile different data models have …
As internet usage rapidly increases in both private and corporate sectors, the study of network intrusion detection is continuously becoming more relevant and has thus been …
Internet of Things (loT) has been playing an important role in many sectors, such as smart cities, smart agriculture, smart healthcare, and smart manufacturing. However, loT de-vices …