1. bookTom 26 (2021): Zeszyt 2 (December 2021)
Informacje o czasopiśmie
License
Format
Czasopismo
eISSN
2255-8691
Pierwsze wydanie
08 Nov 2012
Częstotliwość wydawania
2 razy w roku
Języki
Angielski
Otwarty dostęp

Adversarial Attacks and Defense Technologies on Autonomous Vehicles: A Review

Data publikacji: 30 Dec 2021
Tom & Zeszyt: Tom 26 (2021) - Zeszyt 2 (December 2021)
Zakres stron: 96 - 106
Informacje o czasopiśmie
License
Format
Czasopismo
eISSN
2255-8691
Pierwsze wydanie
08 Nov 2012
Częstotliwość wydawania
2 razy w roku
Języki
Angielski
Abstract

In recent years, various domains have been influenced by the rapid growth of machine learning. Autonomous driving is an area that has tremendously developed in parallel with the advancement of machine learning. In autonomous vehicles, various machine learning components are used such as traffic lights recognition, traffic sign recognition, limiting speed and pathfinding. For most of these components, computer vision technologies with deep learning such as object detection, semantic segmentation and image classification are used. However, these machine learning models are vulnerable to targeted tensor perturbations called adversarial attacks, which limit the performance of the applications. Therefore, implementing defense models against adversarial attacks has become an increasingly critical research area. The paper aims at summarising the latest adversarial attacks and defense models introduced in the field of autonomous driving with machine learning technologies up until mid-2021.

Keywords

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