Are autonomous vehicles driving us to safety? - Understanding adversarial attacks on autonomous vehicle's perception modules

This paper aims to discuss adversarial attacks on Autonomous Vehi- cles (AVs), and the defence mechanisms that can be utilized to prevent such attacks. The paper first focuses on spoofing multiple cameras with overlapping field of view, then moves on to discuss other various feature squeezing counte...

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Main Author: Chan, Jonathan Chew Meng
Other Authors: Anupam Chattopadhyay
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2023
Subjects:
Online Access:https://hdl.handle.net/10356/166136
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1661362023-04-21T15:39:30Z Are autonomous vehicles driving us to safety? - Understanding adversarial attacks on autonomous vehicle's perception modules Chan, Jonathan Chew Meng Anupam Chattopadhyay School of Computer Science and Engineering anupam@ntu.edu.sg Engineering::Computer science and engineering This paper aims to discuss adversarial attacks on Autonomous Vehi- cles (AVs), and the defence mechanisms that can be utilized to prevent such attacks. The paper first focuses on spoofing multiple cameras with overlapping field of view, then moves on to discuss other various feature squeezing countermeasure techniques that can be used to protect AVs from these adversarial attacks. The paper includes experiments that eval- uate the effectiveness of these countermeasures using different scenarios and datasets. The paper also highlight potential future works, including exploring other types of adversarial attacks and implementing adversarial training of neural networks. Bachelor of Engineering (Computer Science) 2023-04-19T07:07:49Z 2023-04-19T07:07:49Z 2023 Final Year Project (FYP) Chan, J. C. M. (2023). Are autonomous vehicles driving us to safety? - Understanding adversarial attacks on autonomous vehicle's perception modules. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/166136 https://hdl.handle.net/10356/166136 en SCSE22-0031 application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Computer science and engineering
spellingShingle Engineering::Computer science and engineering
Chan, Jonathan Chew Meng
Are autonomous vehicles driving us to safety? - Understanding adversarial attacks on autonomous vehicle's perception modules
description This paper aims to discuss adversarial attacks on Autonomous Vehi- cles (AVs), and the defence mechanisms that can be utilized to prevent such attacks. The paper first focuses on spoofing multiple cameras with overlapping field of view, then moves on to discuss other various feature squeezing countermeasure techniques that can be used to protect AVs from these adversarial attacks. The paper includes experiments that eval- uate the effectiveness of these countermeasures using different scenarios and datasets. The paper also highlight potential future works, including exploring other types of adversarial attacks and implementing adversarial training of neural networks.
author2 Anupam Chattopadhyay
author_facet Anupam Chattopadhyay
Chan, Jonathan Chew Meng
format Final Year Project
author Chan, Jonathan Chew Meng
author_sort Chan, Jonathan Chew Meng
title Are autonomous vehicles driving us to safety? - Understanding adversarial attacks on autonomous vehicle's perception modules
title_short Are autonomous vehicles driving us to safety? - Understanding adversarial attacks on autonomous vehicle's perception modules
title_full Are autonomous vehicles driving us to safety? - Understanding adversarial attacks on autonomous vehicle's perception modules
title_fullStr Are autonomous vehicles driving us to safety? - Understanding adversarial attacks on autonomous vehicle's perception modules
title_full_unstemmed Are autonomous vehicles driving us to safety? - Understanding adversarial attacks on autonomous vehicle's perception modules
title_sort are autonomous vehicles driving us to safety? - understanding adversarial attacks on autonomous vehicle's perception modules
publisher Nanyang Technological University
publishDate 2023
url https://hdl.handle.net/10356/166136
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