Data-driven network intrusion detection (NID) has a tendency towards minority attack
classes compared to normal traffic. Many datasets are collected in simulated environments …

Despite the advances reached along the last 20 years, anomaly detection in network
behavior is still an immature technology, and the shortage of commercial tools thus …

Network intrusion detection aims at distinguishing the attacks on the Internet from normal
use of the Internet. It is an indispensable part of the information security system. Due to the …

Zero-day cyber attacks such as worms and spy-ware are becoming increasingly widespread
and dangerous. The existing signature-based intrusion detection mechanisms are often not …

The constant increase of attacks against networks and their resources (as recently shown by
the CodeRed worm) causes a necessity to protect these valuable assets. Firewalls are now …

In this paper we introduce the Hierarchical Intrusion DEtection (HIDE) system, which detects
network-based attacks as anomalies using statistical preprocessing and neural network …

This chapter provides the overview of the state of the art in intrusion detection research.
Intrusion detection systems are software and/or hardware components that monitor …

Current network intrusion detection systems lack adaptability to the frequently changing
network environments. Furthermore, intrusion detection in the new distributed architectures …

With the advent and explosive growth of the global Internet and electronic commerce
environments, adaptive/automatic network/service intrusion and anomaly detection in wide …

This paper introduces the Minnesota Intrusion Detection System (MINDS), which uses a
suite of data mining techniques to automatically detect attacks against computer networks …