With the rapid advancements of ubiquitous information and communication technologies, a large number of trustworthy online systems and services have been deployed. However …
Network security becomes indispensable to our daily interactions and networks. As attackers continue to develop new types of attacks and the size of networks continues to grow, the …
MA Khan, Y Kim - Computers, Materials & Continua, 2021 - cdn.techscience.cn
Machine learning (ML) algorithms are often used to design effective intrusion detection (ID) systems for appropriate mitigation and effective detection of malicious cyber threats at the …
V Hnamte, J Hussain - Telematics and Informatics Reports, 2023 - Elsevier
In recent years, all real-world processes have been shifted to the cyber environment practically, and computers communicate with one another over the Internet. As a result, there …
Detection of intrusions is a system that is competent in detecting cyber-attacks and network anomalies. A variety of strategies have been developed for IDS so far. However, there are …
Attacks on networks are currently the most pressing issue confronting modern society. Network risks affect all networks, from small to large. An intrusion detection system must be …
SM Kasongo - Computer Communications, 2023 - Elsevier
In recent years, the spike in the amount of information transmitted through communication infrastructures has increased due to the advances in technologies such as cloud computing …
K Ren, Y Zeng, Z Cao, Y Zhang - Scientific reports, 2022 - nature.com
Network assaults pose significant security concerns to network services; hence, new technical solutions must be used to enhance the efficacy of intrusion detection systems …
Machine learning techniques are being widely used to develop an intrusion detection system (IDS) for detecting and classifying cyberattacks at the network-level and the host …