A Bayesian Networks in Intrusion Detection Systems

A Bayesian Networks in Intrusion Detection Systems

Intrusion detection systems (IDSs) have been widely used to overcome security threats in computer networks. Anomaly-based approaches have the advantage of being able to detect previously unknown attacks, but they suffer from the difficulty of building robust models of acceptable behaviour which may result in a large number of false alarms caused by incorrect classification of events in current ...

Intrusion Detection using Continuous Time Bayesian Networks

Intrusion detection systems (IDSs) fall into two high-level categories: network-based systems (NIDS) that monitor network behaviors, and host-based systems (HIDS) that monitor system calls. In this work, we present a general technique for both systems. We use anomaly detection, which identifies patterns not conforming to a historic norm. In both types of systems, the rates of change vary dramat...

Bayesian Networks for Network Intrusion Detection

Intrusion Detection in IOT based Networks Using Double Discriminant Analysis

Intrusion detection is one of the main challenges in wireless systems especially in Internet of things (IOT) based networks. There are various attack types such as probe, denial of service, remote to local and user to root. In addition to known attacks and malicious behaviors, there are various unknown attacks that some of them have similar behavior with respect to each other or mimic the norma...

Intrusion Detection in Wireless Sensor Networks using Genetic Algorithm

Wireless sensor networks, due to the characteristics of sensors such as wireless communication channels, the lack of infrastructure and targeted threats, are very vulnerable to the various attacks. Routing attacks on the networks, where a malicious node from sending data to the base station is perceived. In this article, a method that can be used to transfer the data securely to prevent attacks...