This research proposes a measure for assessing the adequacy of DDOS detection systems. DDOS attacks pose serious threats to businesses around the globe. The best defense incorporates a plurality of detection methods. To increase the likelihood that malicious traffic can be effectively identified, multiple detection tests should be used. However, the complexity and quantity of contemporary tests...

DDoS (Distributed Denial-of-Service) attacks detection system deployed in source-end network is superior in detection and prevention than that in victim network, because it can perceive and throttle attacks before data flow to Internet. However, the current existed works in source-end network lead to a high false-positive rate and falsenegative rate for the reason that they are based on single-...

Distributed denial of services (DDoS) attacks post a major threat to Internet security. This paper proposes a distributed system to detect flooding DDoS attacks at the earliest possible time. At the launching stage of a DDoS attack, some changes in traffic fluctuation are detectable at the router or gateway level. We develop a distributed change-point (DCP) detection architecture using change a...

Application layer Distributed Denial of Service (DDoS) attacks are recognized as one of the most damaging attacks on the Internet security today. In our recent work [1], we have shown that unsupervised machine learning can be effectively utilized in the process of distinguishing between regular (human) and automated (web/botnet crawler) visitors to a web site. We have also shown that with a sli...

We propose discrimination methods that classify cluster of traffic behaviour of flash crowds and DDoS attacks such as traffic pattern and characteristics and check cluster randomness. The behavior-based clustering consolidates packet into clusters based on similarity of observed behavior, e.g., source IPs are clustered together based on their pattern of destination port usage. The main objectiv...

In this paper, we propose a simple but robust scheme to detect denial of service attacks (including distributed denial of service attacks) by monitoring the increase of new IP addresses. Unlike previous proposals for bandwidth attack detection schemes which are based on monitoring the traffic volume, our scheme is very effective for highly distributed denial of service attacks. Our scheme explo...

The wireless ad hoc network is particularly vulnerable to DOS attacks due to its features of open medium, dynamic changing topology, cooperative algorithms, decentralization of the protocols, and lack of a clear line of defense is a growing problem in networks today. In Mobile Ad hoc Networks (MANET), various types of Denial of Service Attacks (DOS) are possible because of the inherent limitati...

UDP traffic has recently been used extensively in flooding-based distributed denial of service (DDoS) attacks, most notably by those launched by the Anonymous group. Despite extensive past research in the general area of DDoS detection/prevention, the industry still lacks effective tools to deal with DDoS attacks leveraging UDP traffic. This paper presents our investigation into the proportiona...

We design Distributed Denial of Service (DDoS) detection procedures based on a non Gaussian modeling of the marginal distributions of aggregated Internet traffic. The theoretical and practical relevances of this modeling is illustrated and discussed. From this modeling, various statistical distances (Mean Quadratic Distance of Kullback Divergence) between an observation and a reference time win...