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.
This paper presents an approach to IP traceback based on the probabilistic packet marking paradigm. Our approach, which we call randomize-and-link, uses large checksum cords to ldquolinkrdquo message fragments in a way that is highly scalable, for the checksums serve both as associative addresses and data integrity verifiers. The main advantage of these checksum cords is that they spread the addresses of possible router messages across a spectrum that is too large for the attacker to easily create messages that collide with legitimate messages. Traceback mechanisms are a critical part of the defense against IP spoofing and DoS attacks, as well as being of forensic value to law enforcement. Currently proposed IP traceback mechanisms are inadequate to address the traceback problem for the following reasons: they require DDoS victims to gather thousands of packets to reconstruct a single attack path; they do not scale to large scale distributed DoS attacks; and they do not support incremental deployment. We propose fast Internet traceback (FIT), a new packet marking approach that significantly improves IP traceback in several dimensions: (1) victims can identify attack paths with high probability after receiving only tens of packets, a reduction of 1-3 orders of magnitude compared to previous packet marking schemes; (2) FIT performs well even in the presence of legacy routers, allowing every FIT-enabled router in path to be identified; and (3) FIT scales to large distributed attacks with thousands of attackers. Compared with previous packet marking schemes, FIT represents a step forward in performance and deployability. An improved dynamic probabilistic packet marking algorithm named IDPPM is presented, which not only can locate and attack a source rapidly and accurately, but also can reduce the marking overhead of routers near the attackers, which is its greatest contribution given by our technique. In contrast to previous work, the challenge of weakest node and weakest link is solved with the price of a little more numbers of packets to reconstruct the attack path. Theoretical analysis and NS2 simulation results in IPv4 and IPv6 testify that the approach is feasible and efficient respectively. Index Terms—Distributed Denial of Service (DDoS), IP traceback, Dynamic Probabilistic Packet Marking (DPPM), IPv6 Distributed denial of service attacks continue to pose major threats to the Internet. In order to traceback attack sources (i.e., IP addresses), a well studied approach is probabilistic packet marking (PPM), where each intermediate router of a packet marks it with a certain probability, enabling a victim host to traceback the attack source. In a recent study, we showed how attackers can take advantage of probabilistic nature of packet markings in existing PPM schemes to create spoofed marks, hence compromising traceback. In this paper, we propose a new PPM scheme called TTL-based PPM (TPM) scheme, where each packet is marked with a probability inversely proportional to the distance traversed by the packet so far. Thus, packets that have to traverse longer distances are marked with higher probability, compared to those that have to traverse shorter distances. This ensures that a packet is marked with much higher probability by intermediate routers than by traditional mechanisms, hence reducing the effectiveness of spoofed packets reaching victims. Using formal analysis and simulations using real Internet topology maps, we show how our TPM scheme can effectively trace DDoS attackers even in presence of spoofing when compared to existing schemes.