A tool for tracing network data plane via SDN/OpenFlow

Wang, Yangyang; Bi, Jun; Zhang, Keyao

doi:10.1007/s11432-015-1057-7

Cited by 8 publications

(4 citation statements)

References 16 publications

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“…Wang et al proposed a method capable of tracing data flow in a large-scale multi-domain SDN network [20], which applied transmission path tracing to a larger and more complex network. Gao et al proposed a Universal and RObust in-band PackEt trajectory tracing approach for SDN-enabled networks (UniROPE) [21], which shifted the focus of packet tracing from supporting a single network topology to supporting various network topologies.…”

Section: Faulty Path Detectionmentioning

confidence: 99%

ProbD: Faulty Path Detection Based on Probability in Software-Defined Networking

Yao¹,

Wang²,

Weng³

et al. 2023

Intelligent Automation &Amp; Soft Computing

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With the increasing number of switches in Software-Defined Networking (SDN), there are more and more faults rising in the data plane. However, due to the existence of link redundancy and multi-path forwarding mechanisms, these problems cannot be detected in time. The current faulty path detection mechanisms have problems such as the large scale of detection and low efficiency, which is difficult to meet the requirements of efficient faulty path detection in large-scale SDN. Concerning this issue, we propose an efficient network path fault testing model ProbD based on probability detection. This model achieves a high probability of detecting arbitrary path fault in the form of small-scale random sampling. Under a certain path fault rate, ProbD obtains the curve of sample size and probability of detecting arbitrary path fault by randomly sampling network paths several times. After a small number of experiments, the ProbD model can correctly estimate the path fault rate of the network and calculate the total number of paths that need to be detected according to the different probability of detecting arbitrary path fault and the path fault rate of the network. The final experimental results show that, compared with the full path coverage test, the ProbD model based on probability detection can achieve efficient network testing with less overhead. Besides, the larger the network scale is, the more overhead will be saved.

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Section: Faulty Path Detectionmentioning

confidence: 99%

ProbD: Faulty Path Detection Based on Probability in Software-Defined Networking

Yao¹,

Wang²,

Weng³

et al. 2023

Intelligent Automation &Amp; Soft Computing

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show abstract

“…As we later show, combining these separate tools using a single framework has synergies-e.g., additional information can be uncovered regarding network issues-that would not be available when using them disjointly. We note that other tools, e.g., sTrace [18], could be used for monitoring also.…”

Section: Network Specificationmentioning

confidence: 99%

An Extensible Automated Failure Localization Framework Using NetKAT, Felix, and SDN Traceroute

Pelle

Gulyás

2019

Future Internet

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Designing, implementing, and maintaining network policies that protect from internal and external threats is a highly non-trivial task. Often, troubleshooting networks consisting of diverse entities realizing complex policies is even harder. Software-defined networking (SDN) enables networks to adapt to changing scenarios, which significantly lessens human effort required for constant manual modifications of device configurations. Troubleshooting benefits SDN’s method of accessing forwarding devices as well, since monitoring is made much easier via unified control channels. However, by making policy changes easier, the job of troubleshooting operators is made harder too: For humans, finding, analyzing, and fixing network issues becomes almost intractable. In this paper, we present a failure localization framework and its proof-of-concept prototype that helps in automating the investigation of network issues. Like a controller for troubleshooting tools, our framework integrates the formal specification (expected behavior) and network monitoring (actual behavior) and automatically gives hints about the location and type of network issues by comparing the two types of information. By using NetKAT (Kleene algebra with tests) for formal specification and Felix and SDN traceroute for network monitoring, we show that the integration of these tools in a single framework can significantly ease the network troubleshooting process.

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“…As usually, adversaries can break through or bypass firewalls and intrusion detection systems (IDS) so that an intranet can be easily compromised. As one of revolutionary technologies, Moving Target Defense (MTD) changes game rules, providing a dynamic and proactive network defense [1][2][3].…”

Section: Introductionmentioning

confidence: 99%

CHAOS: An SDN-Based Moving Target Defense System

Shi

Zhang

Wang

et al. 2017

Security and Communication Networks

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Moving target defense (MTD) has provided a dynamic and proactive network defense to reduce or move the attack surface that is available for exploitation. However, traditional network is difficult to realize dynamic and active security defense effectively and comprehensively. Software-defined networking (SDN) points out a brand-new path for building dynamic and proactive defense system. In this paper, we propose CHAOS, an SDN-based MTD system. Utilizing the programmability and flexibility of SDN, CHAOS obfuscates the attack surface including host mutation obfuscation, ports obfuscation, and obfuscation based on decoy servers, thereby enhancing the unpredictability of the networking environment. We propose the Chaos Tower Obfuscation (CTO) method, which uses the Chaos Tower Structure (CTS) to depict the hierarchy of all the hosts in an intranet and define expected connection and unexpected connection. Moreover, we develop fast CTO algorithms to achieve a different degree of obfuscation for the hosts in each layer. We design and implement CHAOS as an application of SDN controller. Our approach makes it very easy to realize moving target defense in networks. Our experimental results show that a network protected by CHAOS is capable of decreasing the percentage of information disclosure effectively to guarantee the normal flow of traffic.

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A tool for tracing network data plane via SDN/OpenFlow

Cited by 8 publications

References 16 publications

ProbD: Faulty Path Detection Based on Probability in Software-Defined Networking

ProbD: Faulty Path Detection Based on Probability in Software-Defined Networking

An Extensible Automated Failure Localization Framework Using NetKAT, Felix, and SDN Traceroute

CHAOS: An SDN-Based Moving Target Defense System

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