A filter algorithm based on ARMA model to suppress the influence of atmospheric disturbance in laser straightness measurement

Yayong, Wang; Liu, ShuJie; Zhang, Shixin; Huang, Yubin; Fan, Kuang‐Chao

doi:10.1117/12.2511948

Cited by 3 publications

(2 citation statements)

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“…The main barrier for using first-principle modeling in the computing system domain is that some unrealistic assumptions are made. For that reason we use empirical approaches for developing transfer functions through autoregressive moving average (ARMA) approach [10]. The proposed feedback control system model relies on having a tuning parameter that is easy to control.…”

Section: Introductionmentioning

confidence: 99%

Towards Securing OpenFlow Controllers for SDNs using ARMA Models

Aly

Kanj

Mostafa

et al. 2022

International Journal of Applied Mathematics, Computational Science and Systems Engineering

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Control layers are moved away from the forwarding switching layers in Software Defined Networks. SDNs allow more programmability and flexibility to the controllers. OpenFlow is a protocol that gives access to the forwarding plane of a network switch or router over the SDN network. OpenFlow uses a centralized control of network switches and routers in SDN environment. Security is of a major importance for SDN deployment. Transport Layer Security (TLS) is be used to implement security for OpenFlow. This paper proposes a new technique to improve the security of the OpenFlow controller through modifying the TLS implementation. The proposed model is referred to as Secured Feedback model using Autoregressive Moving Average (ARMA) for SDN networks (SFBARMASDN). SFBARMASDN depends on computing the feedback for incoming packets based on ARMA models. Filtering techniques based on ARMA techniques are used to filter the packets and detect malicious packets to be dropped. SFBARMASDN is compared to two reference models. One reference model is based on Bayesian and the other reference model is the standard OpenFlow. Results are very promising. SFBARMASDN has outperformed both the secured standard using Bayesian network for SDN (SSBNSDN) and the standard OpenFlow in different scenarios by an average improvement of 7% and 80% respectively. The processing time overhead for the SFBARMASDN increases by only a percentage of 3% and 5% when compared to the SSBNSDN and the standard OpenFlow respectively.

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Section: Introductionmentioning

confidence: 99%

Towards Securing OpenFlow Controllers for SDNs using ARMA Models

Aly

Kanj

Mostafa

et al. 2022

International Journal of Applied Mathematics, Computational Science and Systems Engineering

View full text Add to dashboard Cite

show abstract

“…The main barrier for using first-principle modeling in the computing system domain was that some unrealistic assumptions were made. For that reason we used empirical approaches for developing transfer functions through the autoregressive moving average (ARMA) approach [12]. The proposed feedback control system model relied on having a tuning parameter that was easy to control.…”

Section: Introductionmentioning

confidence: 99%

Feedback ARMA Models versus Bayesian Models towards Securing OpenFlow Controllers for SDNs

Aly

Alabed

2022

Electronics

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In software-defined networking (SDN), the control layers are moved away from the forwarding switching layers. SDN gives more programmability and flexibility to the controllers. OpenFlow is a protocol that gives access to the forwarding plane of a network switch or router over the SDN network. OpenFlow uses a centralized control of network switches and routers in and SDN environment. Security is of major importance for SDN deployment. Transport layer security (TLS) is used to implement security for OpenFlow. This paper proposed a new technique to improve the security of the OpenFlow controller through modifying the TLS implementation. The proposed model is referred to as the secured feedback model using autoregressive moving average (ARMA) for SDN networks (SFBARMASDN). SFBARMASDN depended on computing the feedback for incoming packets based on ARMA models. Filtering techniques based on ARMA techniques were used to filter the packets and detect malicious packets that needed to be dropped. SFBARMASDN was compared to two reference models. One reference model was Bayesian-based and the other reference model was the standard OpenFlow.

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Statistical Simulation of Laser Spot Drift in Non-Kolmogorov Turbulence

赵

2024

AAM

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A filter algorithm based on ARMA model to suppress the influence of atmospheric disturbance in laser straightness measurement

Cited by 3 publications

References 1 publication

Towards Securing OpenFlow Controllers for SDNs using ARMA Models

Towards Securing OpenFlow Controllers for SDNs using ARMA Models

Feedback ARMA Models versus Bayesian Models towards Securing OpenFlow Controllers for SDNs

Statistical Simulation of Laser Spot Drift in Non-Kolmogorov Turbulence

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