The treatment of Internet traffic is increasingly affected by national policies that require the ISPs in a country to adopt common protocols or practices. Examples include government enforced censorship, wiretapping, and protocol deployment mandates for IPv6 and DNSSEC. If an entire nation's worth of ISPs apply common policies to Internet traffic, the global implications could be significant. For instance, how many countries rely on China or Great Britain (known traffic censors) to transit their traffic? These kinds of questions are surprisingly difficult to answer, as they require combining information collected at the prefix, Autonomous System, and country level, and grappling with incomplete knowledge about the AS-level topology and routing policies. In this paper we develop the first framework for country-level routing analysis, which allows us to answer questions about the influence of each country on the flow of international traffic. Our results show that some countries known for their national policies, such as Iran and China, have relatively little effect on interdomain routing, while three countries (the United States, Great Britain, and Germany) are central to international reachability, and their policies thus have huge potential impact.
In addition to 's work @cite_27 discussed earlier, there are at least two other methods for inferring AS-paths that are prefix specific. M " @cite_33 showed that when an AS has multiple routers distributed across many locations, more than one router needs to be simulated to capture all of the routing diversity within the AS. By simulating multiple quasi-routers per AS, they were able to predict AS-paths with relatively high accuracy (reported 65 training data sets makes it difficult to compare the accuracy of their technique with ours. and more computationally efficient. This allowed us to study all 290,000 prefixes rather than the 1000 prefixes reported in M "
@cite_27 @cite_33
2159281894 2162695692 2159326294 1574986862
Inferring AS-level end-to-end paths can be a valu- able tool for both network operators and researchers. A widely known technique for inferring end-to-end paths is to perform traceroute from sources to destinations. Unfortunately, traceroute requires the access to source machines and is resource consuming. In this paper, we propose two algorithms for AS-level end-to-end path inference. The key idea of our algorithm is to exploit the AS paths appeared in BGP routing tables and infer AS paths based on the ones. In addition, our algorithms infer AS paths on the granularity of destination prefix instead of destination AS. That is, we infer AS paths from any source AS to any destination prefix. This is essential since routing in the Internet is determined based on destination prefixes instead of destination ASs. The validation results show that our algorithm yields accuracy up to 95 for exact match and accuracy up to 97 for path length match. We further extend our algorithm to infer a set of potential AS paths between a source AS and a destination prefix. We find that on average, 86 of inferred AS path sets are accurate in the sense that one of the paths in the set matches the actual AS path. Note that our algorithms require BGP routing tables only and do not require additional data trace or access to either sources or destinations. In addition, we demonstrate that the accuracy of this BGP-based inference approach cannot go beyond 90 . As more and more Internet IP prefix hijacking incidents are being reported, the value of hijacking detection services has become evident. Most of the current hijacking detection approaches monitor IP prefixes on the control plane and detect inconsistencies in route advertisements and route qualities. We propose a different approach that utilizes information collected mostly from the data plane. Our method is motivated by two key observations: when a prefix is not hijacked, 1) the hop count of the path from a source to this prefix is generally stable; and 2) the path from a source to this prefix is almost always a super-path of the path from the same source to a reference point along the previous path, as long as the reference point is topologically close to the prefix. By carefully selecting multiple vantage points and monitoring from these vantage points for any departure from these two observations, our method is able to detect prefix hijacking with high accuracy in a light-weight, distributed, and real-time fashion. Through simulations constructed based on real Internet measurement traces, we demonstrate that our scheme is accurate with both false positive and false negative ratios below 0.5 . Despite many efforts over the past decade, the ability to generate topological maps of the Internet at the router-level accurately and in a timely fashion remains elusive. Mapping campaigns commonly involve traceroute-like probing that are usually non-adaptive and incomplete, thus revealing only a portion of the underlying topology. In this paper we demonstrate that standard probing methods yield datasets that implicitly contain information about much more than just the directly observed links and routers. Each probe, in addition to the underlying domain knowledge, returns information that places constraints on the underlying topology, and by integrating a large number of such constraints it is possible to accurately infer the existence of unseen components of the Internet. We describe DomainImpute, a novel data analysis methodology designed to accurately infer the unseen hop-count distances between observed routers. We use both synthetic and a large empirical dataset to validate the proposed methods. On our empirical real world dataset, we show that our methods can estimate over 55 of the unseen distances between observed routers to within a one-hop error. The lack of an accurate representation of the Internet topology at the Autonomous System (AS) level is a limiting factor in the design, simulation, and modeling efforts in inter-domain routing protocols. In this paper, we design and implement a framework for identifying AS links that are missing from the commonly-used Internet topology snapshots. We apply our framework and show that the new links that we find change the current Internet topology model in a non-trivial way. First, in more detail, our framework provides a large-scale comprehensive synthesis of the available sources of information. We cross-validate and compare BGP routing tables, Internet Routing Registries, and traceroute data, while we extract significant newinformation from the less-studied Internet Exchange Points (IXPs). We identify 40 more edges and approximately 300 more peer-to-peer edges compared to commonly used data sets. Second, we identify properties of the new edges and quantify their effects on important topological properties. Given the new peer-to-peer edges, we find that for some ASes more than 50 of their paths stop going through their ISP providers assuming policy-aware routing. A surprising observation is that the degree of a node may be a poor indicator of which ASes it will peer with: the two degrees differ by a factor of four or more in 50 of the peer-to-peer links. Finally, we attempt to estimate the number of edges we may still be missing.