Multiple probabilistic packet marking (PPM) schemes for IP traceback have been proposed to deal with Distributed Denial of Service (DDoS) attacks by reconstructing their attack graphs and identifying the attack sources. In this paper, ten PPM-based IP traceback schemes are compared and analyzed in terms of features such as convergence time, performance evaluation, underlying topologies, incremental deployment, re-marking, and upstream graph. Our analysis shows that the considered schemes exhibit a significant discrepancy in performance as well as performance assessment. We concisely demonstrate this by providing a table showing that (a) different metrics are used for many schemes to measure their performance and, (b) most schemes are evaluated on different classes of underlying network topologies. Our results reveal that both the value and arrangement of the PPM-based scheme convergence times vary depending on exactly the underlying network topology. As a result, this paper shows that a side-by-side comparison of the scheme performance a complicated and turns out to be a crucial open problem in this research area.
In this article we present the current state of the art in IP traceback. The rising threat of cyber attacks, especially DDoS, makes the IP traceback problem very relevant to today's Internet security. Each approach is evaluated in terms of its pros and cons. We also relate each approach to practical deployment issues on the existing Internet infrastructure. The functionality of each approach is discussed in detail and then evaluated. We conclude with a discussion on some legal implications of IP traceback. Because the Internet has been widely applied in various fields, more and more network security issues emerge and catch people's attention. However, adversaries often hide themselves by spoofing their own IP addresses and then launch attacks. For this reason, researchers have proposed a lot of traceback schemes to trace the source of these attacks. Some use only one packet in their packet logging schemes to achieve IP tracking. Others combine packet marking with packet logging and therefore create hybrid IP traceback schemes demanding less storage but requiring a longer search. In this paper, we propose a new hybrid IP traceback scheme with efficient packet logging aiming to have a fixed storage requirement for each router (under 320 KB, according to CAIDA's skitter data set) in packet logging without the need to refresh the logged tracking information and to achieve zero false positive and false negative rates in attack-path reconstruction. In addition, we use a packet's marking field to censor attack traffic on its upstream routers. Lastly, we simulate and analyze our scheme, in comparison with other related research, in the following aspects: storage requirement, computation, and accuracy.  A low-rate distributed denial of service (DDoS) attack has significant ability of concealing its traffic because it is very much like normal traffic. It has the capacity to elude the current anomaly-based detection schemes. An information metric can quantify the differences of network traffic with various probability distributions. In this paper, we innovatively propose using two new information metrics such as the generalized entropy metric and the information distance metric to detect low-rate DDoS attacks by measuring the difference between legitimate traffic and attack traffic. The proposed generalized entropy metric can detect attacks several hops earlier (three hops earlier while the order α = 10 ) than the traditional Shannon metric. The proposed information distance metric outperforms (six hops earlier while the order α = 10) the popular Kullback-Leibler divergence approach as it can clearly enlarge the adjudication distance and then obtain the optimal detection sensitivity. The experimental results show that the proposed information metrics can effectively detect low-rate DDoS attacks and clearly reduce the false positive rate. Furthermore, the proposed IP traceback algorithm can find all attacks as well as attackers from their own local area networks (LANs) and discard attack traffic.  We propose a new approach for IP traceback which is scalable and simple to implement, and introduces no bandwidth and practically no processing overhead. It is backward compatible with equipment which does not implement it. The approach is capable of tracing back attacks, which are composed of just a few packets. In addition, a service provider can implement this scheme without revealing its internal network topology. Finding the source of forged Internet Protocol (IP) datagrams in a large, high-speed network is difficult due to the design of the IP protocol and the lack of sufficient capability in most high-speed, high-capacity router implementations. Typically, not enough of the routers in such a network are capable of performing the packet forwarding diagnostics required for this. As a result, tracking-down the source of a flood-type denial-of-service (DoS) attack is usually difficult or impossible in these networks. CenterTrack is an overlay network, consisting of IP tunnels or other connections, that is used to selectively reroute interesting datagrams directly from edge routers to special tracking routers. The tracking routers, or associated sniffers, can easily determine the ingress edge router by observing from which tunnel the datagrams arrive. The datagrams can be examined, then dropped or forwarded to the appropriate egress point. This system simplifies the work required to determine the ingress adjacency of a flood attack while bypassing any equipment which may be incapable of performing the necessary diagnostic functions. The integrity of the Internet is severely impaired by rampant denial of service and distributed DoS attacks. It is by no means trivial to devise a countermeasure to address these attacks because of their anonymous and distributed nature. This article presents a brief survey of the most promising recently proposed schemes for tracing cyber attacks: IP traceback. Since IP traceback technology is evolving rapidly, for the community to better comprehend and capture the properties of disparate traceback approaches, we first classify these schemes from multiple aspects. From the perspective of practicality and feasibility, we then analyze and explore the advantages and disadvantages of these schemes in depth so that shortcomings and possible enhancements of each scheme are highlighted. Finally, open problems and future work are discussed, and concluding remarks are drawn.