Biblio

Traditional address scanning attacks mainly rely on the naive 'brute forcing' approach, where the entire IPv4 address space is exhaustively searched by enumerating different possibilities. However, such an approach is inefficient for IPv6 due to its vast subnet size (i.e., 264). As a result, it is widely assumed that address scanning attacks are less feasible in IPv6 networks. In this paper, we evaluate new IPv6 reconnaissance techniques in real IPv6 networks and expose how to leverage the Domain Name System (DNS) for IPv6 network reconnaissance. We collected IPv6 addresses from 5 regions and 100,000 domains by exploiting DNS reverse zone and DNSSEC records. We propose a DNS Guard (DNSG) to efficiently detect DNS reconnaissance attacks in IPv6 networks. DNSG is a plug and play component that could be added to the existing infrastructure. We implement DNSG using Bro and Suricata. Our results demonstrate that DNSG could effectively block DNS reconnaissance attacks.

Network attacks have become a growing threat to the current Internet. For the enhancement of network security and accountability, it is urgent to find the origin and identity of the adversary who misbehaves in the network. Some studies focus on embedding users' identities into IPv6 addresses, but such design cannot support the Stateless Address Autoconfiguration (SLAAC) protocol which is widely deployed nowadays. In this paper, we propose SDN-Ti, a general solution to traceback and identification for attackers in IPv6 networks based on Software Defined Network (SDN). In our proposal, the SDN switch performs a translation between the source IPv6 address of the packet and its trusted ID-encoded address generated by the SDN controller. The network administrator can effectively identify the attacker by parsing the malicious packets when the attack incident happens. Our solution not only avoids the heavy storage overhead and time synchronism problems, but also supports multiple IPv6 address assignment scenarios. What's more, SDN-Ti does not require any modification on the end device, hence can be easily deployed. We implement SDN-Ti prototype and evaluate it in a real IPv6 testbed. Experiment results show that our solution only brings very little extra performance cost, and it shows considerable performance in terms of latency, CPU consumption and packet loss compared to the normal forwarding method. The results indicate that SDN-Ti is feasible to be deployed in practice with a large number of users.

Linking the growing IPv6 deployment to existing IPv4 addresses is an interesting field of research, be it for network forensics, structural analysis, or reconnaissance. In this work, we focus on classifying pairs of server IPv6 and IPv4 addresses as siblings, i.e., running on the same machine. Our methodology leverages active measurements of TCP timestamps and other network characteristics, which we measure against a diverse ground truth of 682 hosts. We define and extract a set of features, including estimation of variable (opposed to constant) remote clock skew. On these features, we train a manually crafted algorithm as well as a machine-learned decision tree. By conducting several measurement runs and training in cross-validation rounds, we aim to create models that generalize well and do not overfit our training data. We find both models to exceed 99% precision in train and test performance. We validate scalability by classifying 149k siblings in a large-scale measurement of 371k sibling candidates. We argue that this methodology, thoroughly cross-validated and likely to generalize well, can aid comparative studies of IPv6 and IPv4 behavior in the Internet. Striving for applicability and replicability, we release ready-to-use source code and raw data from our study.