ANOMALY & ATTACK DETECTION IN IOT SENSOR DATA USING GATED RECURRENT UNIT AND PARTICLE SWARM OPTIMIZATION TECHNIQUES

Authors

  • VIPIN Professor (Dr.) Mukesh Singla

Keywords:

Internet of Things, Anomaly detection, IoT security, Machine learning, Deep learning, Cyber security, Gated Recurrent Unit etc.

Abstract

Internet of Things (IoT)-connected technologies are becoming more and more important to a number of public and commercial businesses. The integrity of data and the availability of services are often the targets of security threats that target the networks and devices that make up the IoT

References

I. Makhdoom, M. Abolhasan, J. Lipman, R.P. Liu, W. Ni, Anatomy of threats to the internet of things, IEEE Commun. Surv. Tutor. 21 (2) (2018) 1636–1675.

I. Cvitić, D. Peraković, M. Periša, M. Botica, Novel approach for detection of IoT generated DDoS traffic, Wirel. Netw. 27 (3) (2021) 1573–1586.

Y.-Q. Chen, B. Zhou, M. Zhang, C.-M. Chen, Using IoT technology for computer integrated manufacturing systems in the semiconductor industry, Appl. Soft Comput. 89 (2020) 106065.

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Published

2023-04-21

How to Cite

VIPIN Professor (Dr.) Mukesh Singla. (2023). ANOMALY & ATTACK DETECTION IN IOT SENSOR DATA USING GATED RECURRENT UNIT AND PARTICLE SWARM OPTIMIZATION TECHNIQUES. Journal of Computational Analysis and Applications (JoCAAA), 31(2), 378–408. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/2120

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Articles

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