Adversarial Human Activity Recognition Using Wi-Fi CSI
Adversarial Human Activity Recognition Using Wi-Fi CSI
复制标题
DOI：
10.1109/ccece53047.2021.9569098
复制
发表时间：
2021-09
期刊：
影响因子：
--
通讯作者：
Harshit Ambalkar;Xuyu Wang;S. Mao
中科院分区：
文献类型：
--
作者：
Harshit Ambalkar;Xuyu Wang;S. Mao
人类活动识别已经用于物联网中的各种应用（例如，健康监测、安全和运动相关监测）。Wi-Fi信道状态信息（CSI）被广泛用于活动识别，其中CSI可以捕获影响无线信道的人类活动。在本文中，我们研究了对抗性攻击对基于深度神经网络（DNN）的Wi-Fi CSI人类活动识别的影响。首先，我们讨论了系统框架，其中活动识别可以被认为是一个分类问题，并引入了一个特定的DNN模型。然后，我们讨论了基于DNN的人类活动识别的对抗性攻击问题，并制定了三种白盒攻击。在公共Wi-Fi CSI数据集的实验中，我们的结果表明，基于DNN的人类活动分类的性能受到三种白盒对抗攻击的极大影响。
Human activity recognition has been used for various applications in Internet of Things (e.g., health monitoring, security, and sport-related monitoring). Wi-Fi channel state information (CSI) is widely used for activity recognition, where CSI can capture human activities that influence wireless channel. In this paper, we study the impact of adversarial attacks on deep neural network (DNN) based human activity recognition with Wi-Fi CSI. First, we discuss the system framework, where activity recognition can be considered as a classification problem and a specific DNN model is introduced. Then, we discuss adversarial attack problem for DNN-based human activity recognition and formulate three white-box attacks. In the experiment with a public Wi-Fi CSI dataset, our results show that the performances of DNN-based human activity classification are greatly influenced by three white-box adversarial attacks.