Identification of Gradient-Based Attacks on Autonomous Vehicle Traffic Recognition System Using Statistical Method

Author:

Sanapala Lavanya,Gondi LakshmeeswariORCID

Publisher

Springer Nature Switzerland

Reference20 articles.

1. R.B. Mrinal, M.S. Javed, Autonomous driving architectures: Insights of machine learning and deep learning algorithms. Mach. Learn. Appl. 6, 100164 (2021)

2. B.W. Safat, A.A. Majid, A.H. Mahammad, H. Aini, A.S. Salina, J.K. Pin, B.M. Muhamad, Vision-based traffic sign detection and recognition systems: Current trends and challenges. Sensors 19, 2093 (2019)

3. B. Preeti, A. Kunjal, Traffic sign classification using CNN. Int. J. Res. Appl. Sci. Eng. Technol. 10(II) (2022) ISSN: 2321-9653; IC Value: 45.98; SJ Impact Factor: 7.538

4. J.G. Ian, S. Jonathon, S. Christian, Explaining and Harnessing Adversarial Examples (Published as a conference paper at ICLR 2015, 2015)

5. Z. Jindi, L. Yang, W. Jianping, W. Kui, L. Kejie, J. Xiaohua, Evaluating adversarial attacks on driving safety in vision-based autonomous vehicles. IEEE Internet Things J. 5(9) (2022)

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