Distributed Denial of Service (DDoS) attacks can be so powerful that they can easily deplete the computing resources or bandwidth of the potential targets, by flooding massive packets. Internet infrastructures and network applications, including social services and communication systems for emergency management, are under the threat of the DDoS problem. This thesis aims at providing efficient m...

This work proposes a novel approach to infer and characterize Internet-scale DNS Distributed Reflection Denial of Service (DRDoS) attacks by leveraging the darknet space. Complementary to the pioneer work on inferring Distributed Denial of Service (DDoS) activities using darknet, this work shows that we can extract DDoS activities without relying on backscattered analysis. The aim of this work ...

DDoS attacks are highly distributed, well coordinated, offensive assaults on services, hosts, and infrastructure of the Internet. Effective defensive countermeasures to DDoS attacks will require equally sophisticated, well coordinated, monitoring, analysis, and response. The Cossack project is developing an architecture to explore such coordination using multicast, annotated topology informatio...

Distributed denial of service (DDoS) attack is a continuous critical threat to the Internet. Derived from the low layers, new application-layer-based DDoS attacks utilizing legitimate HTTP requests to overwhelm victim resources are more undetectable. The case may be more serious when such attacks mimic or occur during the flash crowd event of a popular Website. Focusing on the detection for suc...

Distributed denial-of-service (DDoS) could be a rapidly growing drawback. The multitude and sort of each the attacks and the defense approaches is overwhelming. This paper is a survey on the drawback of denial-of-service (DoS) and Distributed Denial of Service (DDoS) attacks and projected ways in which to deal with it. we tend to describe the character of the matter and look for its root causes...

Increased instances of distributed denial of service (DDoS) attacks on the Internet have raised questions on whether and how ad hoc networks are vulnerable to such attacks. This paper studies the special properties of such attacks in ad hoc networks. We examine two types of area-congestion-based DDoS attacks – remote and local attacks – and present in-depth analysis on various factors and attac...

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...

Title of dissertation: DETECTING DDoS ATTACKS IN STUB DOMAINS Christopher Kommareddy, Doctor of Philosophy, 2006 Dissertation directed by: Prof. Samrat Bhattacharjee Department of Computer Science Dr. Richard La Department of Electrical & Computer Engineering DoS attacks have least impact when detected and mitigated close to the attacks’ source. This is more important for Distributed DoS (DDoS)...

Distributed Denial of Service attacks (DDoS) have remained as one of the most destructive attacks in the Internet for over two decades. Despite tremendous efforts on the design of DDoS defense strategies, few of them have been considered for widespread deployment due to strong design assumptions on the Internet infrastructure, prohibitive operational costs and complexity. Recently, the emergenc...

In this paper we present and evaluate a Radial-basis-function neural network detector for Distributed-Denial-of-Service (DDoS) attacks in public networks based on statistical features estimated in short-time window analysis of the incoming data packets. A small number of statistical descriptors were used to describe the DDoS attacks behaviour, and an accurate classification is achieved using th...