Network Identification via Node Knockout

Nabi-Abdolyousefi, Marzieh; Mesbahi, Mehran

doi:10.1109/tac.2012.2200376

Cited by 74 publications

(42 citation statements)

References 11 publications

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“…Port knocking is an authentication technique used by network administrators [11][12][13]. It consists of a specified sequence of closed port connection attempts to specific IP addresses called a knock sequence.…”

Section: Introductionmentioning

confidence: 99%

Lightweight edge authentication for software defined networks

et al. 2020

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OpenFlow is considered as the most known protocol for Software Defined Networking (SDN). The main drawback of OpenFlow is the lack of support of new header definitions, which is required by network operators to apply new packet encapsulations. While SDN's logically centralized control plane could enhance network security by providing global visibility of the network state, it still has many side effects. The intelligent controllers that orchestrate the dumb switches are overloaded and become prone to failure. Delegating some level of control logic to the edge or, to be precise, the switches can offload the controllers from local state based decisions that do not require global network wide knowledge. Thus, this paper, to the best of our knowledge, is the first to propose the delegation of typical security functions from specialized middleboxes to the data plane. We leverage the opportunities offered by programming protocol-independent packet processors (P4) language to present two authentication techniques to assure that only legitimate nodes are able to access the network. The first technique is the port knocking and the second technique is the One-Time Password. Our experimental results indicate that our proposed techniques improve the network overall availability by offloading the controller as well as reducing the traffic in the network without noticeable negative impact on switches' performance.

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Section: Introductionmentioning

confidence: 99%

Lightweight edge authentication for software defined networks

et al. 2020

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“…Centralized methods have been first introduced. In [2], a grounding procedure where a node broadcasts a zero state to its neighbors without being removed from a consensus network was introduced. This node knockout approach follows the same spirit than the gene-knockout procedure used in experimental biology for identifying interactions in gene networks.…”

Section: Introductionmentioning

confidence: 99%

Distributed network topology reconstruction in presence of anonymous nodes

Tran

Kibangou

2015

2015 23rd European Signal Processing Conference (EUSIPCO)

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This paper concerns the problem of reconstructing the network topology from data propagated through the network by means of an average consensus protocol. The proposed method is based on the distributed estimation of graph Laplacian spectral properties. Precisely, the identification of the network topology is implemented by estimating both eigenvalues and eigenvectors of the consensus matrix, which is related to the graph Laplacian matrix. In this paper, we focus the exposition on the estimation of the eigenvectors since the eigenvalues estimation can be achieved based on recent results of the literature using the same kind of data. We show how the topology can be reconstructed in presence of anonymous nodes, i.e. nodes that do not disclose their ID.

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“…Uncovering the relationship between dynamics and network structure has indeed relevant applications in biology (biochemical, neural and ecological networks), finance, computer science (Internet and World Wide Web), transportation (delivery and distribution networks), and electrical engineering (power grids). In [3], the interaction geometry among a known number of agents adopting (weighted) consensus-type algorithms for their coordination, is reconstructed using a grounding procedure inspired by experimental biology, called "node knockout" (see also [4]), while in [5] the consensus matrix is determined from its eigenstructure estimated in a distributed fashion. Stochastic methods have lately emerged as powerful alternatives to the deterministic ones in [3][4][5]: the main idea here is to reconstruct the network topology from noise-contaminated time series collected at each node of the graph.…”

Section: Introductionmentioning

confidence: 99%

“…In [3], the interaction geometry among a known number of agents adopting (weighted) consensus-type algorithms for their coordination, is reconstructed using a grounding procedure inspired by experimental biology, called "node knockout" (see also [4]), while in [5] the consensus matrix is determined from its eigenstructure estimated in a distributed fashion. Stochastic methods have lately emerged as powerful alternatives to the deterministic ones in [3][4][5]: the main idea here is to reconstruct the network topology from noise-contaminated time series collected at each node of the graph. Noise is ubiquitous, e.g., in biological networks and relying on such a natural variability as a noninvasive network-identification tool appears extremely promising [6].…”

Section: Introductionmentioning

confidence: 99%

A distributed solution to the network reconstruction problem

Morbidi

Kibangou

2014

Systems & Control Letters

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It has been recently shown in [1] that by collecting noise-contaminated time series generated by a coupled-oscillator system at each node of a network, it is possible to robustly reconstruct its topology, i.e. determine the graph Laplacian. Restricting ourselves to linear consensus dynamics over undirected communication networks, in this paper we introduce a new dynamic average consensus least-squares algorithm to locally estimate these time series at each node, thus making the reconstruction process fully distributed and more easily applicable in the real world. We also propose a novel efficient method for separating the off-diagonal entries of the reconstructed Laplacian, and examine several concepts related to the trace of the dynamic correlation matrix of the coupled single integrators, which is a distinctive element of our network reconstruction method. The theory is illustrated with examples from computer, power and transportation systems.

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Network Identification via Node Knockout

Cited by 74 publications

References 11 publications

Lightweight edge authentication for software defined networks

Lightweight edge authentication for software defined networks

Distributed network topology reconstruction in presence of anonymous nodes

A distributed solution to the network reconstruction problem

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