BASAR:Black-box Attack on Skeletal Action Recognition

TL;DR

This paper introduces BASAR, the first black-box adversarial attack method for skeletal action recognition, demonstrating its effectiveness and revealing vulnerabilities in current models under realistic attack scenarios.

Contribution

The paper presents a novel black-box attack method for skeletal action recognition and provides insights into model vulnerabilities and robustness.

Findings

BASAR successfully attacks multiple models and data modes.

Adversarial samples are common on-manifold in skeletal motions.

Effective and imperceptible attacks are achievable.

Abstract

Skeletal motion plays a vital role in human activity recognition as either an independent data source or a complement. The robustness of skeleton-based activity recognizers has been questioned recently, which shows that they are vulnerable to adversarial attacks when the full-knowledge of the recognizer is accessible to the attacker. However, this white-box requirement is overly restrictive in most scenarios and the attack is not truly threatening. In this paper, we show that such threats do exist under black-box settings too. To this end, we propose the first black-box adversarial attack method BASAR. Through BASAR, we show that adversarial attack is not only truly a threat but also can be extremely deceitful, because on-manifold adversarial samples are rather common in skeletal motions, in contrast to the common belief that adversarial samples only exist off-manifold. Through exhaustive evaluation and comparison, we show that BASAR can deliver successful attacks across models, data, and attack modes. Through harsh perceptual studies, we show that it achieves effective yet imperceptible attacks. By analyzing the attack on different activity recognizers, BASAR helps identify the potential causes of their vulnerability and provides insights on what classifiers are likely to be more robust against attack. Code is available at https://github.com/realcrane/BASAR-Black-box-Attack-on-Skeletal-Action-Recognition.