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 …

Network monitoring is a major building block for many domains in communication networks.
Besides typical accounting mechanisms and the emerging area of charging in next …

Flow-level traffic measurement is required for a wide range of applications including
accounting, network planning and security management. A key design challenge is how to …

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

Investigating network flows is an approach of detecting attacks by identifying known
patterns. Flow statistics are used to discover anomalies by aggregating network traces and …

Multiple network-wide anomaly detection techniques proposed in the literature define an
anomaly as a statistical outlier in aggregated network traffic. The most popular way to …

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 …

Anomalies generate vast amounts of bogus traffic, which can overwhelm the network and
any attached hosts. Identifying traffic anomalies rapidly and accurately is critical to network …

The increased usage of Internet, E-business, and social network enables attack behaviour
with diverse fashions. A Network Intrusion Detection System (NIDS) is software which can …

Network traffic anomaly detection is an important component in network security and
management domains which can help to improve availability and reliability of networks. This …