On the Hardness of Topology Inference

Acharya, H. B.; Gouda, Mohamed G.

doi:10.1007/978-3-642-17679-1_22

Cited by 7 publications

(12 citation statements)

References 9 publications

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“…DICT maintains the invariant that there are never two nodes u, v which are not kconnected in the currently requested graph H while they are k-connected in H; no path relevant for the connectivity of the current component is overlooked and needs to be found later. Subsequently, nodes and edges which are not contributing to the connectivity of the current component can then be discovered by (1) edge expansion where additional nodes of degree two are added along a motif edge, and by (2) adding sequences of motifs to the nodes iteratively with the same process. Figure 2 gives a simplified overview of our discovery strategy: in a first phase, we seek to discover the highly connected parts of the physical network (and reserve the corresponding resources, see Lemma 4); this is achieved by trying to embed sequences of so-called "motifs" of the highest connectivity and subsequently shifting toward less connected motifs.…”

Section: Motif Frameworkmentioning

confidence: 99%

“…The classic instrument to discover Internet topologies is traceroute [7], but the tool has several problems which renders the problem challenging. One complication of traceroute stems from the fact that routers may appear as stars (i.e., anonymous nodes), which renders the accurate characterization of Internet topologies difficult [1,23,30]. Network tomography is another important field of topology discovery.…”

Section: Related Workmentioning

confidence: 99%

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Adversarial topology discovery in network virtualization environments: a threat for ISPs?

2014

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Network virtualization is a new Internet paradigm which allows multiple virtual networks (VNets) to share the resources of a given physical infrastructure. The virtualization of entire networks is the natural next step after the virtualization of nodes and links.While the problem of how to embed a VNet ("guest network") on a given resource network ("host network") is algorithmically well-understood, much less is known about the security implications of this new technology. This paper introduces a new model to reason about one particular security threat: the leakage of information about the physical infrastructure-often a business secret.We initiate the study of this new problem and introduce the notion of request complexity which describes the number of VNet requests needed to fully disclose the substrate topology. We derive lower bounds and present algorithms achieving an asymptotically optimal request complexity for important graph classes such as trees, cactus graphs (complexity O(n)) as well as arbitrary graphs (complexity O(n 2 )). Moreover, a general motif-based topology discovery framework is described which exploits the poset structure of the VNet embedding relation.

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Section: Motif Frameworkmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Adversarial topology discovery in network virtualization environments: a threat for ISPs?

2014

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“…In [1], hardness results are derived for this model. However, as pointed out by the authors themselves, the irregular node model-where nodes are anonymous due to high loads-is less relevant in practice and hence they consider strictly anonymous nodes in their follow-up studies [2]. As proved in [2], the problem is still hard (in the sense that there are many minimal networks corresponding to a trace set), even with only two anonymous nodes, symmetric routing and without aliasing.…”

Section: Related Workmentioning

confidence: 99%

Misleading Stars: What Cannot Be Measured in the Internet?

Pignolet

Schmid

Trédan

2011

Lecture Notes in Computer Science

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Abstract. Traceroute measurements are one of the main instruments to shed light onto the structure and properties of today's complex networks such as the Internet. This paper studies the feasibility and infeasibility of inferring the network topology given traceroute data from a worst-case perspective, i.e., without any probabilistic assumptions on, e.g., the nodes' degree distribution. We attend to a scenario where some of the routers are anonymous, and propose two fundamental axioms that model two basic assumptions on the traceroute data: (1) each trace corresponds to a real path in the network, and (2) the routing paths are at most a factor 1/α off the shortest paths, for some parameter α ∈ (0, 1]. In contrast to existing literature that focuses on the cardinality of the set of (often only minimal) inferrable topologies, we argue that a large number of possible topologies alone is often unproblematic, as long as the networks have a similar structure. We hence seek to characterize the set of topologies inferred with our axioms. We introduce the notion of star graphs whose colorings capture the differences among inferred topologies; it also allows us to construct inferred topologies explicitly. We find that in general, inferrable topologies can differ significantly in many important aspects, such as the nodes' distances or the number of triangles. These negative results are complemented by a discussion of a scenario where the trace set is best possible, i.e., "complete". It turns out that while some properties such as the node degrees are still hard to measure, a complete trace set can help to determine global properties such as the connectivity.

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“…The classic instrument to discover Internet topologies is traceroute [4], but the tool has several problems which makes the problem challenging. One complication of traceroute stems from the fact that routers may appear as stars (i.e., anonymous nodes), which renders the accurate characterization of Internet topologies difficult [1,10,13]. Network tomography is another important field of topology discovery.…”

Section: Introductionmentioning

confidence: 99%

Request Complexity of VNet Topology Extraction: Dictionary-Based Attacks

Pignolet

Schmid

Trédan³

2013

Networked Systems

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Abstract. The network virtualization paradigm envisions an Internet where arbitrary virtual networks (VNets) can be specified and embedded over a shared substrate (e.g., the physical infrastructure). As VNets can be requested at short notice and for a desired time period only, the paradigm enables a flexible service deployment and an efficient resource utilization. This paper investigates the security implications of such an architecture. We consider a simple model where an attacker seeks to extract secret information about the substrate topology, by issuing repeated VNet embedding requests. We present a general framework that exploits basic properties of the VNet embedding relation to infer the entire topology. Our framework is based on a graph motif dictionary applicable for various graph classes. Moreover, we provide upper bounds on the request complexity, the number of requests needed by the attacker to succeed.

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On the Hardness of Topology Inference

Cited by 7 publications

References 9 publications

Adversarial topology discovery in network virtualization environments: a threat for ISPs?

Adversarial topology discovery in network virtualization environments: a threat for ISPs?

Misleading Stars: What Cannot Be Measured in the Internet?

Request Complexity of VNet Topology Extraction: Dictionary-Based Attacks

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