396e3d57186c1f28fcb-7d26 20230310075954711 beie:beie director@blueeyesintelligence.org WEB-FORM International Journal of Recent Technology and Engineering (IJRTE) IJRTE 22773878 10.35940/ijrte.2277-3878 https://www.ijrte.org/ 03 30 2023 11 6 Department of Electronics and Communication, Deccan College of Engineering and Technology, Hyderabad (Telangana), India Dr. Syeda Kausar Fatima https://orcid.org/0009-0006-9700-8966 Dr. Syeda Gauhar Fatima Department of Electronics and Communication, Deccan College of Engineering and Technology, Hyderabad (Telangana), India Deep convolutional networks have proven practical for autonomous vehicle applications as deep CNN technology has advanced. There has been a growing vogue for using end-to-end computational methods for the mechanization of vehicular activities. Preliminary studies, though, have demonstrated that deep learning network classifiers are sensitive to adversarial approaches. But, the impact of adversarial strategies on regression problems is not sufficiently known. We propose two white-box direct security breaches targeting progressive self-driving vehicles in this research. A prediction model is used in the navigation mechanism, which receives a picture as feed and returns a steering angle. By altering the input image, we may influence the actions of the automated driving unit. Two different attacks may be launched in practice on CPUs with no need for GPUs. The effectiveness of the threats is demonstrated by trials carried out in Udacity. 03 30 2023 84 90 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true No, I did not receive. No conflicts of interest to the best of our knowledge. No, the article does not require ethical approval and consent to participate with evidence. Not relevant. All authors have equal participation in this article. 10.35940/ijrte.F7482.0311623 https://www.ijrte.org/portfolio-item/F74820311623/