Anomaly detection (AD) use within the network intrusion detection field of research, or
network intrusion AD (NIAD), is dependent on the proper use of similarity and distance …

Benchmark datasets are heavily depended upon by the research community to validate
theoretical findings and track progression in the state-of-the-art. NIDS dataset creation …

With an increase in the number and types of network attacks, traditional firewalls and data
encryption methods can no longer meet the needs of current network security. As a result …

Intrusion detection can identify unknown attacks from network traffics and has been an
effective means of network security. Nowadays, existing methods for network anomaly …

Host-based anomaly intrusion detection system design is very challenging due to the
notoriously high false alarm rate. This paper introduces a new host-based anomaly intrusion …

Intrusion detection systems are generally tested using datasets compiled at the end of last
century, justified by the need for publicly available test data and the lack of any other …

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 …

In this paper, a hybrid method of support vector machine and genetic algorithm (GA) is
proposed and its implementation in intrusion detection problem is explained. The proposed …

Network intrusion detection problem is an ongoing challenging research area because of a
huge number of traffic volumes, extremely imbalanced data sets, multi-class of attacks …

In January of 2010, I met Sam and Klaus at the inaugural International Conference on
Performance Engineering (ICPE), in San Jose, USA. I gave the keynote address “Software …