Sensor and Decision Fusion-Based Intrusion Detection and Mitigation Approach for Connected Autonomous Vehicles-Reference-Cited by-同舟云学术

Sensor and Decision Fusion-Based Intrusion Detection and Mitigation Approach for Connected Autonomous Vehicles

Published:2024-07-01 Issue:13 Volume:24 Page:20908-20919
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Moradi Milad¹^ORCID,Kordestani Mojtaba¹^ORCID,Jalali Mahsa¹^ORCID,Rezamand Milad¹^ORCID,Mousavi Mehdi¹^ORCID,Chaibakhsh Ali²^ORCID,Saif Mehrdad¹^ORCID

Affiliation:

1. Department of Electrical and Computer Engineering, University of Windsor, Windsor, ON, Canada

2. Faculty of Mechanical Engineering, University of Guilan, Rasht, Iran

Funder

Natural Sciences and Engineering Research Council of Canada

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/7361/10577556/10534169.pdf?arnumber=10534169

Reference35 articles.

1. Anomaly Detection in Automated Vehicles Using Multistage Attention-Based Convolutional Neural Network

2. LSTM-Based Intrusion Detection System for In-Vehicle Can Bus Communications

3. Exploiting Consistency Among Heterogeneous Sensors for Vehicle Anomaly Detection

4. Adventures in automotive networks and control units;Miller;Def. Con.,2013

5. Smart anomaly detection in sensor systems: A multi-perspective review

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