With the ever increasing deployment and usage of gigabit networks, traditional network
anomaly detection based Intrusion Detection Systems (IDS) have not scaled accordingly …

As the communication industry has connected distant corners of the globe using advances
in network technology, intruders or attackers have also increased attacks on networking …

In this paper, we present a novel Flow-based Statistical Aggregation Schemes (FSAS) for
Network Anomaly Detection. An IP flow is a unidirectional series of IP packets of a given …

In this paper, we present the design and implementation of a new approach for anomaly
detection and classification over high speed networks. The proposed approach is based first …

Current network monitoring systems rely strongly on signa-ture-based and supervised-
learning-based detection methods to hunt out network attacks and anomalies. Despite being …

The anomaly-based network intrusion detection systems (IDS) typically suffer from high false
alarm rate rendering them useless in practice as the subsequent analysis done by the …

Traditional network anomaly detection involves developing models that rely on packet
inspection. However, increasing network speeds and use of encrypted protocols make per …

In this article we discuss the design and implementation of a real-time parallel anomaly
detection system. The key idea is to use multiple existing anomaly detection algorithms in …

Network anomaly detection is a classically difficult research topic in intrusion detection.
However, existing research has been solely focused on the detection algorithm. An …

Algorithms for anomaly detection in IP networks have been developed and a real-time
distributed platform for anomaly detection has been implemented. These algorithms …