Intrusion Detection System in Internet of Vehicles using Machine Learning

Registration ID: IJNRD_190729

Published ID: IJNRD2304168

DOI: Click Here to Get

Deepika Karri , Ramanjaneyulu Bandi , Sandeep Maharana , Nikhil Bontu , Mrs. G. Gayathri

Internet of vehicles, Cyber-attacks, Prediction Confidence, LightGBM, XGBoost, CatBoost

Intelligent Transportation Systems (ITSs) utilise autonomous vehicles (AVs) as a promising technology to increase the efficiency and safety. Vehicle-to-everything (V2X) technology makes it possible for cars and other infrastructure to communicate. However, AVs and the Internet of Vehicles (IoV) are prone to various cyberattacks, including spoofing, sniffer, and denial of service attacks. The proposed intrusion detection system can detect different cyberattacks in the AV networks, according to the results of its implementation on standard data sets. It is created by determining the top-performing ML model for each class of attack from among three ML algorithms (XGBoost, LightGBM, and CatBoost). To accurately decide how to detect different forms of cyberattacks, the class alpha model and its prediction confidence values are used. Moreover, the proposed approaches allow the system to simultaneously achieve high detection rate and low computational cost.

Published Paper   E-Certificate

Deepika Karri, Ramanjaneyulu Bandi, Sandeep Maharana, Nikhil Bontu, & Mrs. G. Gayathri (April-2023). Intrusion Detection System in Internet of Vehicles using Machine Learning. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(4), b478-b484. https://ijnrd.org/papers/IJNRD2304168.pdf

Volume 8 Issue 4, April-2023

Pages : b478-b484

Paper Reg. ID: IJNRD_190729

Published Paper Id: IJNRD2304168

Downloads: 000121977

Research Area: Computer Engineering 

Country: medchal-malkajgiri, Telangana, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2304168.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2304168

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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