Journal ArticleDOI
WiAdv
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TLDR
The attack case study and analysis reveal the vulnerability of WiFi-based gesture recognition systems, and it is hoped WiAdv could help promote the improvement of the relevant systems.Abstract:
WiFi-based gesture recognition systems have attracted enormous interest owing to the non-intrusive of WiFi signals and the wide adoption of WiFi for communication. Despite boosted performance via integrating advanced deep neural network (DNN) classifiers, there lacks sufficient investigation on their security vulnerabilities, which are rooted in the open nature of the wireless medium and the inherent defects (e.g., adversarial attacks) of classifiers. To fill this gap, we aim to study adversarial attacks to DNN-powered WiFi-based gesture recognition to encourage proper countermeasures. We design WiAdv to construct physically realizable adversarial examples to fool these systems. WiAdv features a signal synthesis scheme to craft adversarial signals with desired motion features based on the fundamental principle of WiFi-based gesture recognition, and a black-box attack scheme to handle the inconsistency between the perturbation space and the input space of the classifier caused by the in-between non-differentiable processing modules. We realize and evaluate our attack strategies against a representative state-of-the-art system, Widar3.0 in realistic settings. The experimental results show that the adversarial wireless signals generated by WiAdv achieve over 70% attack success rate on average, and remain robust and effective across different physical settings. Our attack case study and analysis reveal the vulnerability of WiFi-based gesture recognition systems, and we hope WiAdv could help promote the improvement of the relevant systems.read more
Citations
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Wi-Fi Localization Obfuscation: An implementation in openwifi
TL;DR: In this article , the authors present the implementation of a location obfuscation technique within the openwifi project that enables fine manipulation of the radio signal at transmitter side and yields acceptable, if not good, performance.
Journal ArticleDOI
VoiceCloak
Meng Chen,Liwang Lu,Junhao Xia Wang,Jiadi Yu,Ying Chen,Zhibo Wang,Zhongjie Ba,Feng Lin,Kui Ren +8 more
TL;DR: Zhang et al. as mentioned in this paper proposed a human-centric voice de-identification system, which uses adversarial examples to balance the privacy and utility of voice services, instead of typical additive examples inducing perceivable distortions, they design a novel convolutional adversarial example that modulates perturbations into real-world room impulse responses.
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Ubiquitous WiFi and Acoustic Sensing: Principles, Technologies, and Applications
TL;DR: In this article , the authors conduct a survey of existing work to introduce their underlying principles, proposed technologies, and practical applications, and discuss some open issues of this research area, including hardware restriction, robustness, and applicability.
Journal ArticleDOI
VoiceCloak: Adversarial Example Enabled Voice De-Identification with Balanced Privacy and Utility
TL;DR: Zhang et al. as discussed by the authors proposed a human-centric voice de-identification system, which uses adversarial examples to balance the privacy and utility of voice services, instead of typical additive examples inducing perceivable distortions, they design a novel convolutional adversarial example that modulates perturbations into real-world room impulse responses.
References
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Proceedings ArticleDOI
Practical Black-Box Attacks against Machine Learning
TL;DR: This work introduces the first practical demonstration of an attacker controlling a remotely hosted DNN with no such knowledge, and finds that this black-box attack strategy is capable of evading defense strategies previously found to make adversarial example crafting harder.
Journal ArticleDOI
Tool release: gathering 802.11n traces with channel state information
TL;DR: The measurement setup comprises the customized versions of Intel's close-source firmware and open-source iwlwifi wireless driver, userspace tools to enable these measurements, access point functionality for controlling both ends of the link, and Matlab scripts for data analysis.
Proceedings ArticleDOI
Whole-home gesture recognition using wireless signals
TL;DR: WiSee is presented, a novel gesture recognition system that leverages wireless signals (e.g., Wi-Fi) to enable whole-home sensing and recognition of human gestures and achieves this goal without requiring instrumentation of the human body with sensing devices.
Posted Content
Practical Black-Box Attacks against Machine Learning
TL;DR: In this article, a black-box attack strategy consists in training a local model to substitute for the target DNN, using inputs synthetically generated by an adversary and labeled by the targeted DNN.
Proceedings ArticleDOI
E-eyes: device-free location-oriented activity identification using fine-grained WiFi signatures
TL;DR: This paper presents device-free location-oriented activity identification at home through the use of existing WiFi access points and WiFi devices (e.g., desktops, thermostats, refrigerators, smartTVs, laptops) in a low-cost system that can uniquely identify both in-place activities and walking movements across a home by comparing them against signal profiles.