Machine Learning-Based Intrusion Detection System for Controller Area Networks-Reference-Cited by-同舟云学术

Machine Learning-Based Intrusion Detection System for Controller Area Networks

Published:2020-11-16 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 10th ACM Symposium on Design and Analysis of Intelligent Vehicular Networks and Applications
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Author:

Minawi Omar¹,Whelan Jason¹,Almehmadi Abdulaziz²,El-Khatib Khalil¹

Affiliation:

1. Ontario Tech University, Oshawa, ON, Canada

2. University of Tabuk, Tabuk, Saudi Arabia

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3416014.3424581

Reference27 articles.

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2. Henry Claypool Amitai Bin-Nun and Gerlach Jeffrey. 2017. Self-Driving Cars: The Impact on People with Disabilities. Ruderman Family Foundation White Papers (01 2017). Henry Claypool Amitai Bin-Nun and Gerlach Jeffrey. 2017. Self-Driving Cars: The Impact on People with Disabilities. Ruderman Family Foundation White Papers (01 2017).

3. Examining privacy in vehicular ad-hoc networks

4. CSS Electronics. 2020. CAN Bus Explained - A Simple Intro (2020). https://www.csselectronics.com/screen/page/simple-intro-to-can-bus/language/en CSS Electronics. 2020. CAN Bus Explained - A Simple Intro (2020). https://www.csselectronics.com/screen/page/simple-intro-to-can-bus/language/en

5. E Frank MA Hall and IH Witten. [n.d.]. The WEKA Workbench. Online Appendix for" Data Mining: Practical Machine Learning Tools and Techniques" 2016. E Frank MA Hall and IH Witten. [n.d.]. The WEKA Workbench. Online Appendix for" Data Mining: Practical Machine Learning Tools and Techniques" 2016.

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