Fingerprinting Internet DNS Amplification DDoS Activities

This work proposes a novel approach to infer and characterize Internet-scale DNS amplification DDoS 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 is to extract cyber security intelligence related to DNS Amplification DDoS activities such as detection period, attack duration, intensity, packet size, rate and geo-location in addition to various network-layer and flow-based insights. To achieve this task, the proposed approach exploits certain DDoS parameters to detect the attacks. We empirically evaluate the proposed approach using 720 GB of real darknet data collected from a /13 address space during a recent three months period. Our analysis reveals that the approach was successful in inferring significant DNS amplification DDoS activities including the recent prominent attack that targeted one of the largest anti-spam organizations. Moreover, the analysis disclosed the mechanism of such DNS amplification DDoS attacks. Further, the results uncover high-speed and stealthy attempts that were never previously documented. The case study of the largest DDoS attack in history lead to a better understanding of the nature and scale of this threat and can generate inferences that could contribute in detecting, preventing, assessing, mitigating and even attributing of DNS amplification DDoS activities.Comment: 5 pages, 2 figure

Network domain entrypoint/path determination for DDoS attacks

Accepted versio

Non-intrusive IP Traceback for DDoS Attacks

The paper describes a Non-Intrusive IP traceback scheme which uses sampled traffic under non-attack conditions to build and maintains caches of the valid source addresses transiting network routers. Under attack conditions, route anomalies are detected by determining which routers have been used for unknown source addresses, in order to construct the attack graph. Results of simulation studies are presented. Our approach does not require changes to the Internet routers or protocols. Precise information regarding the attack is not required allowing a wide variety of DDoS attack detection techniques to be used. Our algorithm is simple and efficient, allowing for a fast traceback and the scheme is scalable due to the distribution of processing workload. Copyright 2007 ACM

Locating Network Domain Entry and Exit point/path for DDoS Attack Traffic

A method to determine entry and exit points or paths of DDoS attack traffic flows into and out of network domains is proposed. We observe valid source addresses seen by routers from sampled traffic under non-attack conditions. Under attack conditions, we detect route anomalies by determining which routers have been used for unknown source addresses, to construct the attack paths. We consider deployment issues and show results from simulations to prove the feasibility of our scheme. We then implement our Traceback mechanism in C++ and more realistic experiments are conducted. The experiments show that accurate results, with high traceback speed of a few seconds, are achieved. Compared to existing techniques, our approach is non-intrusive, not requiring any changes to the Internet routers and data packets. Precise information regarding the attack is not required allowing a wide variety of DDoS attack detection techniques to be used. The victim is also relieved from the traceback task during an attack. The scheme is simple and efficient, allowing for a fast traceback, and scalable due to the distribution of processing workload. © 2009 IEEE.Accepted versio