Secure IoT: Deep Learning-Based Intrusion Detection for Attack Detection and Prevent

DOI

https://www.doi.org/10.59256/ijsreat.20240404002

Published In

Volume 4, Issue 4 (2024)

Published Online

July-August 2024

Pages

06-08

Article Type

Research Article

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Nowadays, the wide adoption of the modern Internet of Things (IoT) paradigm has brought about the tremendous development of smart cities. Smart cities operate in real-time world to promote ease and also the human life quality with regard to efficiency and comfort. A security concern along with privacy is considered as a foremost issue in several smart cities. there is basically a requirement for Intrusion Detection Systems for mitigating the IoT-related security outbreaks which took the entire benefits of security liabilities. In existing works, the accuracy in the procedure of detection and security are the main challenge. The non-attacked data is sent to user in a secured way using Improved RSA scheme. After which the user gets and decrypts them. The decrypted data is then forecasted for further examination. The experimental outcomes of proposed techniques employed in Feature Selection, classification, and also secure data transmission are related with the traditional methods.