APA
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Patel, S. K., Sadhwani, S., Muthalagu, R., & Pawar, P. M. (2023). Deep Learning Based Intrusion Detection Systems Techniques in IoT - Survey. 2023 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE).
Chicago/Turabian
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Patel, Samay Kalpesh, Sapna Sadhwani, Raja Muthalagu, and Pranav Mothabhau Pawar. “Deep Learning Based Intrusion Detection Systems Techniques in IoT - Survey.” 2023 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE) (2023).
MLA
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Patel, Samay Kalpesh, et al. “Deep Learning Based Intrusion Detection Systems Techniques in IoT - Survey.” 2023 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE), 2023.
BibTeX Click to copy
@article{samay2023a,
title = {Deep Learning Based Intrusion Detection Systems Techniques in IoT - Survey},
year = {2023},
journal = {2023 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE)},
author = {Patel, Samay Kalpesh and Sadhwani, Sapna and Muthalagu, Raja and Pawar, Pranav Mothabhau}
}
Industry 4.0 is changing the way we communicate and operate as a society, its bringing changes in technologies, industries and a part of this industry Internet of Thing (IoT), they are devices which communicate with each other and are being integrated slowly in all sectors. this creates number of concerns especially towards security and privacy. Cyber intrusion attacks form a major part of the concern as it compromises integrity of sensitive data and are growing in volume with variations increasing rapidly. High complexity of such intrusion attacks has defeated most of the traditional defense techniques This paper focuses on exploring research that was conducted in area of IoT security, specifically in improvement of Intrusion detection system using Deep learning techniques. The results and methods are also discussed which can form a potential base for further research.