Controller Based Proxy for Handling NDP in OpenFlow Network

Sumadi, Fauzi Dwi Setiawan; Chandranegara, Didih Rizki

doi:10.22219/kinetik.v4i1.720

Cited by 2 publications

(3 citation statements)

References 15 publications

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“…System design related to network performance testing on the network architecture, both using SDN and without SDN. The steps taken in this study with references from the literatures [13], [16] as can be seen in flowchart Figure 6. To build a computer network design in Faculty of Engineering UMM-based on Software Define Network, there are some of the main constituent components, namely: (a) Control Plane, a server which served as the control center of the network Software Define Network.…”

Section: Methodsmentioning

confidence: 99%

“…OpenFlow is an open standard maintained by the Open Networking Foundation (ONF). OpenFlow is a protocol for Controller that can modify the behaviour of network devices through "forwarding instruction set" that is well defined [13]. Floodlight is designed to work with a number of switches, routers, virtual switches, and access points that support the OpenFlow standard [14].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Software Defined Networks: a Comparative Study and Quality of Services Evaluation

Nugroho

Irfan

Faruq

2019

SJI

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Software-Defined Network (SDN) as architecture network that separates the control and forwarding functions, so that network operators and administrators can configure the networks in a simple and centrally between thousands of devices. This study is designed and evaluate the Quality of Services (QoS) performances between the two networks employed SDN-based architecture and without SDN-based. MinNet as a software emulator used as a data plane in the network Software Define Network. In this study, comparison of the value of the QoS on the network based on Software Defined Network and traditional network during the test run from the source node is investigated. Network testing by using traffic loads. Traffic loads are used starting from 20Mbps-100Mbps. The result is verified that the QoS analysis of the Software-Defined Network architecture performed better than conventional network architectures. The value of the latency delay on the Software Define Network range between 0,019-0,084ms, and with 0% packet loss when addressed the network traffics of 10-100Mbps.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Software Defined Networks: a Comparative Study and Quality of Services Evaluation

Nugroho

Irfan

Faruq

2019

SJI

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“…SDN is a network paradigm that separates control planes and data planes to solve problems on traditional networks [1] [2]. Control plane is responsible for configuring, including managing traffic flow, while the data plane is responsible for running all the rules defined by the controller [3].…”

Section: Introductionmentioning

confidence: 99%

SDN-Honeypot Integration for DDoS Detection Scheme Using Entropy

Kilwalaga

Sumadi

Syaifuddin

2020

KINETIK

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Limitations on traditional networks contributed to the development of a new paradigm called Software Defined Network (SDN). The separation of control and data plane provides an advantage as well as a security gap on the SDN network because all controls are centralized on the controller so when the compilation of attacks are directed the controller, the controller will be overburdened and eventually dropped. One of the attacks that can be used is the DDoS attack - ICMP Flood. ICMP Flood is an attack intended to overwhelm the target with a large number of ICMP requests. To overcome this problem, this paper proposes detection and mitigation using the Modern Honey Network (MHN) integration in SDN and then makes reactive applications outside the controller using the entropy method. Entropy is a statistical method used to calculate the randomness level of an incoming packet and use header information as a reference for its calculation. In this study, the variables used are the source of IP, the destination of IP and protocol. The results show that detection and mitigation were successfully carried out with an average value of entropy around 10.830. Moreover, CPU usage either in normal packet delivery or attacks showed insignificant impact from the use of entropy. In addition, it can be concluded that the best data collected in 30 seconds in term of the promptness of mitigation flow installation.

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Controller Based Proxy for Handling NDP in OpenFlow Network

Cited by 2 publications

References 15 publications

Software Defined Networks: a Comparative Study and Quality of Services Evaluation

Software Defined Networks: a Comparative Study and Quality of Services Evaluation

SDN-Honeypot Integration for DDoS Detection Scheme Using Entropy

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