Vulnerabilities in Autonomous Driving Technology

Physical Backdoor Attack can Jeopardize Driving with Vision-Large-Language Models

Authors: Zhenyang Ni, Rui Ye, Yuxi Wei, Zhen Xiang, Yanfeng Wang, Siheng Chen | Published: 2024-04-19 | Updated: 2024-04-22
Backdoor Attack
Vulnerabilities in Autonomous Driving Technology
2024.04.19 2025.05.27
Literature Database

Experimental Validation of Sensor Fusion-based GNSS Spoofing Attack Detection Framework for Autonomous Vehicles

Authors: Sagar Dasgupta, Kazi Hassan Shakib, Mizanur Rahman | Published: 2024-01-02
GNSS Security
LSTM Model Performance Evaluation
Vulnerabilities in Autonomous Driving Technology
2024.01.02 2025.05.27
Literature Database

Explaining RADAR features for detecting spoofing attacks in Connected Autonomous Vehicles

Authors: Nidhi Rastogi, Sara Rampazzi, Michael Clifford, Miriam Heller, Matthew Bishop, Karl Levitt | Published: 2022-03-01
Dataset evaluation
Model Design and Accuracy
Vulnerabilities in Autonomous Driving Technology
2022.03.01 2025.05.28
Literature Database

Deep Bayesian Learning for Car Hacking Detection

Authors: Laha Ale, Scott A. King, Ning Zhang | Published: 2021-12-17
Machine Learning Method
Deep Learning Method
Vulnerabilities in Autonomous Driving Technology
2021.12.17 2025.05.28
Literature Database