@inproceedings {Van2015, title = {MPLS Under the Microscope: Revealing Actual Transit Path Diversity}, booktitle = {Internet Measurement Conference (IMC)}, year = {2015}, month = {10/2015}, abstract = {

Traffic Engineering (TE) is one of the keys for improving packet forwarding in\ the Internet. It allows IP network operators to finely tune their forwarding\ paths according to various customer needs. One of the most popular tool\ available today for optimizing the use of networking resources is MPLS. On the\ one hand, operators may use MPLS and label distribution mechanisms such as RSVP-TE\ in conjunction with BGP to define multiple transit paths (for a given edge pair)
verifying different constraints on their network. On the other hand, when\ operators simply enable LDP for distributing MPLS labels in order to improve the\ scalability of their network, another kind of path diversity may appear thanks\ to the ECMP feature of IGP routing.

In this paper, using an MPLS labels analysis, we demonstrate that it is possible\ to better understand the transit path diversity deployed within a given ISP.\ More specifically, we introduce the Label Pattern Recognition (LPR) algorithm, a\ method for analyzing traceroute data including MPLS information. LPR reveals\ the actual usage of MPLS according to the inferred label distribution protocol and\ is able to make the distinction between ECMP and TE multi-path forwarding.\ Based on an extensive and longitudinal traceroute dataset obtained from CAIDA,
we apply LPR and find that each ISP behavior is really specific in regard to its\ MPLS usage. In particular, we are able to observe independently for each ISP\ the MPLS path diversity and usage, and its evolution over time.\ Globally speaking, the main outcomes of our study are that (i) the usage of\ MPLS has been increasing over the the last five years with basic encapsulation\ being predominant, (ii) path diversity is mainly provided thanks to ECMP and\ LDP, and, (iii), TE using MPLS is as common as MPLS without path diversity.

}, keywords = {ECMP, LDP, MPLS, multipath, network discovery, RSVP-TE, traceroute, traffic engineering}, author = {Yves Vanaubel and Pascal M{\'e}rindol and Jean-Jacques Pansiot and Benoit Donnet} } @inproceedings {Van2013, title = {Network Fingerprinting: TTL-Based Router Signature}, booktitle = {ACM/USENIX Internet Measurement Conference (IMC)}, year = {2013}, month = {10/2013}, address = {Barcelona, Spain}, abstract = {

Fingerprinting networking equipment has many potential applications and benefits\ in network management and security. More generally, it is useful for the\ understanding of network structures and their behaviors. In this paper, we\ describe a simple fingerprinting mechanism based on the initial TTL values used\ by routers to reply to various probing messages. We show that main classes
obtained using this simple mechanism are meaningful to distinguish routers\ platforms. Besides, it comes at a very low additional cost compared to standard\ active topology discovery measurements. As a proof of concept, we apply our\ method to gain more insight on the behavior of MPLS routers and to, thus, more\ accurately quantify their visible/invisible deployment.

}, keywords = {fingerprinting, initial TTL, MPLS router signature, network discovery}, doi = {10.1145/2504730.2504761}, author = {Yves Vanaubel and Jean-Jacques Pansiot and Pascal M{\'e}rindol and Benoit Donnet} } @inproceedings {Van2013a, title = {Network Fingerprinting: TTL-Based Router Signatures}, booktitle = {ACM Internet Measurement Conference (IMC)}, year = {2013}, month = {10/2013}, address = {Barcelona, Spain}, abstract = {

Fingerprinting networking equipment has many potential applications and benefits\ in network management and security. More generally, it is useful for the\ understanding of network structures and their behaviors. In this paper, we\ describe a simple fingerprinting mechanism based on the initial TTL values used\ by routers to reply to various probing messages. We show that main classes\ obtained using this simple mechanism are meaningful to distinguish routers
platforms. Besides, it comes at a very low additional cost compared to standard\ active topology discovery measurements. As a proof of concept, we apply our\ method to gain more insight on the behavior of MPLS routers and to, thus, more\ accurately quantify their visible/invisible deployment.

}, keywords = {fingerprinting, initial TTL, MPLS, network discovery, router signatures}, author = {Yves Vanaubel and Jean-Jacques Pansiot and Pascal M{\'e}rindol and Benoit Donnet} } @inproceedings {Det2013, title = {Revealing Middlebox Interference with Tracebox}, booktitle = {ACM/USENIX Internet Measurement Conference (IMC)}, year = {2013}, month = {10/2013}, abstract = {

Middleboxes such as firewalls, NAT, proxies, or Deep Pack-et Inspection play an\ increasingly important role in various types of IP networks, including\ enterprise and cellular networks. Recent studies have shed the light on their\ impact on real traffic and the complexity of managing them. Network operators\ and researchers have few tools to understand the impact of those boxes on any
path. In this paper, we propose tracebox, an extension to the widely used\ traceroute tool, that is capable of detecting various types of middlebox\ interference over almost any path. \ tracebox sends IP packets containing TCP\ segments with different TTL values and analyses the packet encapsulated in the\ returned ICMP messages. Further, as recent routers quote, in the ICMP message,\ the entire IP packet that they received, tracebox is able to detect any\ modification performed by upstream middleboxes. In addition, tracebox can often\ pinpoint the network hop where the middlebox interference occurs. We evaluate\ tracebox with measurements performed on PlanetLab nodes. Our analysis reveals\ various types of middleboxes that were not expected on such an experimental\ testbed supposed to be connected to the Internet without any restriction.

}, keywords = {middlebox, network discovery, tracebox}, doi = {10.1145/2504730.2504757}, author = {Gregory Detal and Benjamin Hesmans and Olivier Bonaventure and Yves Vanaubel and Benoit Donnet} }