Internet services are vulnerable to flooding attacks that lead to denial of service. This paper
proposes a new framework to detect anomalies and to provide early alerts for flooding …

Flooding attacks detection in traffic of backbone networks requires generally the analysis of
a huge amount of data with high accuracy and low complexity. In this paper, we propose a …

With the rapid dependency on the Internet for business, and the fast spread of powerful
destructive DoS/DDoS attack tools, the detection and thwarting of these attacks is primordial …

Distributed denial of service attacks have become both prevalent and sophisticated. Botnet-
driven attacks can be launched from thousands of worm-infected and compromised …

This paper deals with the detection of flooding attacks which are the most common type of
Denial of Service (DoS) attacks. We compare 2 divergence measures (Hellinger distance …

An anomaly detection procedure is defined and its statistical performance are carefully
quantified. It is based on a non Gaussian modeling of the marginal distributions of random …

This paper presents an automated detection method based on classification of network
traffic using predefined set of network metrics. We proposed the set of metrics with focus on …

Intrusion detection systems are one of the necessities of networks to identify the problem of
network attacks. Organizations striving to protect their data from intruders are often …

Recently, a botnet based DDoS (Distributed Denial of Service) attack, called target link
flooding attack, has been reported that cuts off specific links over the Internet and …

Network-based intrusion detection is traditionally bound to deep packet inspection, ie
searching for known signatures of attacks in the packet payload. With the rise of connected …