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.
The IP traceback is an important mechanism in defending against distributed denial-of-service (DDoS) attacks. In this paper, we propose a probabilistic packet marking (PPM) scheme, Tabu Marking Scheme (TMS), to speedup IP traceback. The key idea of "tabu mark" is that, a router still marks packets probabilistically, but regards a packet marked by an upstream router as a tabu and does not mark it again. We study the impact of the traffic aggregation on the convergence behavior of PPM schemes. Furthermore we derive a new analytical result on the partial coupon collection problem, which is a powerful tool applicable for computing the mean convergence time of any PPM scheme. Our study shows that the idea of "tabu mark" not only helps a PPM scheme that allows overwriting to reduce the convergence time under a DDoS attack, but also ensures the authentication of the routers' markings.