학술논문
Real-Time Robust Video Object Detection System Against Physical-World Adversarial Attacks
Document Type
Periodical
Author
Source
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst. Computer-Aided Design of Integrated Circuits and Systems, IEEE Transactions on. 43(1):366-379 Jan, 2024
Subject
Language
ISSN
0278-0070
1937-4151
1937-4151
Abstract
DNN-based video object detection (VOD) powers autonomous driving and video surveillance industries with rising importance and promising opportunities. However, adversarial patch attack yields huge concern in live vision tasks because of its practicality, feasibility, and powerful attack effectiveness. This work proposes Themis, a software/hardware system to defend against adversarial patches for real-time robust VOD. We observe that adversarial patches exhibit extremely localized superficial feature importance in a small region with nonrobust predictions, and thus propose the adversarial region detection algorithm for adversarial effect elimination. Themis also proposes a systematic design to efficiently support the algorithm by eliminating redundant computations and memory traffics. Experimental results show that the proposed methodology can effectively recover the system from the adversarial attack with negligible hardware overhead.