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Detection of interruption attack in the wireless networked closed loop industrial control systems

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Abstract

Due to tremendous growth in the network, security is a major concern and it is gaining a high level of attention in the system. In the Industrial control systems such as SCADA wind turbines, intruders target to corrupt information by making traffic. A Novel method known as Mesh Intruder detachment scheme has proposed to overcome such influential attacks. Enhanced intrusion detection based traffic optimization and deep learning based neural network algorithm are used to detect delay and passage caused by the intruders. The proposed scheme acts in two phases. In the first phase, redundant information such as unwanted distortions, frequency specification changes was removed and selected features were extracted for optimization. In the second phase, an Interruption attack has been detected and labeled which causes damage to the growth of production.

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Abbreviations

EID-TO:

Enhanced intrusion detection based traffic optimization

DL-NN:

Deep learning based neural network algorithm

SCADA:

Supervisory control and data acquisition

IDS:

Intrusion detection system

FDR:

Flight data recorder

PPV:

Prediction of peak velocity

FDR:

False detection rate

NPV:

Net present value

STO:

Surplus training optimization

GA:

Graphical artificial intelligence

TP:

True positive

TN:

True negative

FP:

False positive

FP:

False negative

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Acknowledgment

This research work has been confidentially acknowledged by Anna University recognized research center lab at V V College of Engineering, Tisaiyanvilai, India.

Funding

The data needed for the research work is taken from Gamesa Wind turbines. Since in Wind Turbines traffic based attacks and time delay based interruption attacks cause huge damage which leads to the growth in production, Real-time data stored in SCADA are taken and analyzed.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, V V College of Engineering, Tisaiyanvilai, India

    R. B. Benisha & S. Raja Ratna

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  1. R. B. Benisha
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  2. S. Raja Ratna
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Correspondence to R. B. Benisha.

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Competing interests

R B. Benisha and Dr. S. Raja Ratna declare that they have no Competing interests.

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This article does not contain any studies with animal subjects performed by any of the authors.

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Mesh Intruder detachment scheme workflow in SCADA

Mesh Intruder detachment scheme workflow in SCADA

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Benisha, R.B., Raja Ratna, S. Detection of interruption attack in the wireless networked closed loop industrial control systems. Telecommun Syst 73, 359–370 (2020). https://doi.org/10.1007/s11235-019-00614-3

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