Abstract
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.
Original language | English |
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Title of host publication | Proceedings of 3rd IEEE International Conference on Computational Intelligence and Knowledge Economy, ICCIKE 2023 |
Editors | Anand Kumar, Ved Prakash Mishra, Vishal Naranje, Apurv Yadav |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 53-58 |
Number of pages | 6 |
ISBN (Electronic) | 9798350338263 |
DOIs | |
State | Published - 2023 |
Externally published | Yes |
Event | 3rd IEEE International Conference on Computational Intelligence and Knowledge Economy, ICCIKE 2023 - Dubai, United Arab Emirates Duration: 9 Mar 2023 → 10 Mar 2023 |
Publication series
Name | Proceedings of 3rd IEEE International Conference on Computational Intelligence and Knowledge Economy, ICCIKE 2023 |
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Conference
Conference | 3rd IEEE International Conference on Computational Intelligence and Knowledge Economy, ICCIKE 2023 |
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Country/Territory | United Arab Emirates |
City | Dubai |
Period | 9/03/23 → 10/03/23 |
Bibliographical note
Publisher Copyright:© 2023 IEEE.
Keywords
- Cyber-Attacks
- Deep learning
- IDS
- IoT
- IoT Architecture
- Security