Phantom-CSI Attacks against Wireless Liveness Detection
Authors: 
Qiuye He, Song FangAuthors Info & Claims
Pages 440 - 454
Abstract
All systems monitoring human behavior in real time are, by their nature, attractive targets for spoofing. For example, misdirecting live-feed security cameras or voice-controllable Internet-of-Things (IoT) systems (e.g., Amazon Alexa and Google Assistant) has immediately intuitive benefits, so there is a consequent need for detecting liveness of the human(s) whose behavior is being monitored. Emerging research lines have focused on analyzing changes in prevalent wireless signals to detect video or voice spoofing attacks, as wireless-based techniques do not require the user to carry any additional device or sensor for liveness detection. Video/voice streaming and coexisting wireless signals convey different aspects of the same overall contextual information related to human activities, and the presence of spoofing attacks on the former breaks this relationship, so the latter performs well as liveness detection to augment the former. However, we recognize and herein evaluate how to spoof the latter as well to defeat this liveness detection. In our attack, an adversary can easily create phantom wireless signals and synchronize them with spoofed video/voice signals, such that the legitimate user can no longer distinguish real from fake human activity. Real-world experimental results on top of software-defined radio platforms validate the possibility of generating fake CSI flows and demonstrate that with the phantom-CSI attack, the true positive rates (TPRs) of wireless liveness detection systems for video and voice decrease from 100% spoofing detection to just 4.4% and 0, respectively.
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Index Terms
- Phantom-CSI Attacks against Wireless Liveness Detection
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October 2023
769 pages
ISBN:9798400707650
DOI:10.1145/3607199
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Published: 16 October 2023
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RAID 2023: The 26th International Symposium on Research in Attacks, Intrusions and Defenses
October 16 - 18, 2023
Hong Kong, China
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