Adversarial Attacks and Defenses Toward AI-Assisted UAV Infrastructure Inspection

Author:

Raja Ashok1,Njilla Laurent2,Yuan Jiawei1ORCID

Affiliation:

1. Department of Computer and Information Science, University of Massachusetts Dartmouth, North Dartmouth, MA, USA

2. Air Force Research Laboratory, Information Institute, Rome, NY, USA

Funder

Visiting Faculty Research Program (VFRP) with the Information Assurance Branch of the AFRL, Rome, NY and the Information Institute

U.S. NSF Award

UMass Dartmouth Cybersecurity Center Fellowship

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Computer Science Applications,Hardware and Architecture,Information Systems,Signal Processing

Reference40 articles.

1. SoK: Security and Privacy in Machine Learning

2. On the convergence and robustness of adversarial training;wang;Proc 36th Int Conf Mach Learn,2019

3. Feasibility of inconspicuous GAN-generated adversarial patches against object detection;pavlitskaya;arXiv 2207 07347,2022

4. Playing Against Deep-Neural-Network-Based Object Detectors: A Novel Bidirectional Adversarial Attack Approach

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