The popularity of using Internet contains some risks of network attacks. Intrusion detection is
one major research problem in network security, whose aim is to identify unusual access or …

Intrusion detection based upon computational intelligence is currently attracting
considerable interest from the research community. Characteristics of computational …

The demand for Internet security has escalated in the last two decades because the rapid
proliferation in the number of Internet users has presented attackers with new detrimental …

The aim of an intrusion detection systems (IDS) is to detect various types of malicious
network traffic and computer usage, which cannot be detected by a conventional firewall …

Machine Learning has been steadily gaining traction for its use in Anomaly-based Network
Intrusion Detection Systems (A-NIDS). Research into this domain is frequently performed …

Intrusion detection is a necessary step to identify unusual access or attacks to secure
internal networks. In general, intrusion detection can be approached by machine learning …

Nowadays, the medical tourism industry encourages many healthcare practitioners to
provide high-quality and low-cost medical services for patients worldwide. The development …

The deployment of wireless sensor networks and mobile ad-hoc networks in applications
such as emergency services, warfare and health monitoring poses the threat of various …

In recent years, machine learning (ML) has become an important part to yield security and
privacy in various applications. ML is used to address serious issues such as real-time …

None of the previously proposed Network Intrusion Detection Systems (NIDSs), which are
subject to fuzzy association rules, can meet real-time requirements because they all apply …