Automatic network intrusion detection has been an important research topic for the last
20years. In that time, approaches based on signatures describing intrusive behavior have …

The growing prevalence of network attacks is a well-known problem which can impact the
availability, confidentiality, and integrity of critical information for both individuals and …

The rapid advances in the internet and communication fields have resulted in a huge
increase in the network size and the corresponding data. As a result, many novel attacks are …

An Intrusion Detection System (IDS) is a software that monitors a single or a network of
computers for malicious activities (attacks) that are aimed at stealing or censoring …

This article describes an experimental investigation into the inter-dataset generalization of
supervised machine learning methods, trained to distinguish between benign and several …

This survey paper describes a focused literature survey of machine learning (ML) and data
mining (DM) methods for cyber analytics in support of intrusion detection. Short tutorial …

Recently, computer networks faced a big challenge, which is that various malicious attacks
are growing daily. Intrusion detection is one of the leading research problems in network …

Cyber threats and data breaches have become more sophisticated and stealthier over time.
Traditional rule-based intrusion detection systems fail to detect many modern attacks. This …

The evolution in the attack scenarios has been such that finding efficient and optimal
Network Intrusion Detection Systems (NIDS) with frequent updates has become a big …