Harnessing Generative Modeling and Autoencoders Against Adversarial Threats in Autonomous Vehicles

The safety and security of Autonomous Vehicles (AVs) have been an active area of interest and study in recent years. To enable human behavior, Deep Learning (DL) and Machine Learning (ML) models are extensively used to make accurate decisions. However, the DL and ML models are susceptible to various...

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Veröffentlicht in:	IEEE transactions on consumer electronics Jg. 70; H. 3; S. 6216 - 6223
Hauptverfasser:	Raja, Kathiroli, Theerthagiri, Sudhakar, Swaminathan, Sriram Venkataraman, Suresh, Sivassri, Raja, Gunasekaran
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.08.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Adversarial attacks Autonomous vehicles Closed box Decisions Deep learning generative denoising autoencoders Glass box Machine learning neural structured learning Noise Noise reduction Perturbation methods Training Vehicles
ISSN:	0098-3063, 1558-4127
Online-Zugang:	Volltext
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