SaTC: CORE: Small: Exploiting Stimulus-response Correlation for Wireless Hidden Device Localization

SaTC：核心：小：利用刺激响应相关性进行无线隐藏设备定位

• 批准号: 2155181
• 负责人: Song Fang
• 金额: $ 50万
• 依托单位: University of Oklahoma Norman Campus
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-10-01 至 2025-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2155181&HistoricalAwards=false
• 关键词: SaTC; CORE; Small; Exploiting; Stimulus

Smart Internet-of-things (IoT) devices, such as wireless cameras and voice-controlled devices, commonly employ motion or voice activity detection for increased security and convenience, so that upon detecting physical stimuli (e.g., motion or sound), they start to work and upload the sensing data to the cloud. The ubiquity of such devices also brings privacy concerns associated with unauthorized monitoring, as they can be kept hidden easily in various locations like hotel rooms. Traditional ways to detect a wireless hidden device mainly include Radio Frequency (RF) scanning, lens detection, and physical search. The latter two methods are cumbersome as they require inspecting every corner of the target area. RF scanning may work when the device is actively transmitting, but existing work can only detect a sensor's existence, not its exact location. However, detection is often insufficient, as the device owner may claim it is somewhere outside of the room or installed by others. By finding the physical device, a victim whose privacy is violated can obtain direct and solid evidence.This project focuses on investigating causality between stimuli to hidden wireless devices and resultant patterns in observable wireless traffic. This research aims at (i) designing practical approaches to pinpoint wireless hidden devices leveraging the correlation between artificial stimuli and resultant wireless traffic, and (ii) developing countermeasures against stimulus-response-based device localization schemes. The project will create techniques that substantially safeguard user privacy against unauthorized monitoring via wireless hidden devices. The results from this research will be openly shared.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

智能物联网（IoT）设备（诸如无线相机和语音控制设备）通常采用运动或语音活动检测来提高安全性和便利性，使得在检测到物理刺激（例如，运动或声音），它们开始工作并将传感数据上传到云端。这种设备的普遍存在也带来了与未经授权的监控相关的隐私问题，因为它们可以很容易地隐藏在酒店房间等各种位置。传统的检测无线隐藏设备的方法主要包括射频（RF）扫描、透镜检测和物理搜索。后两种方法很麻烦，因为它们需要检查目标区域的每个角落。当设备正在主动发送时，RF扫描可能会起作用，但现有的工作只能检测传感器的存在，而不是其确切位置。然而，检测通常是不够的，因为设备所有者可能会声称它在房间外的某个地方或由其他人安装。通过找到物理设备，隐私被侵犯的受害者可以获得直接和可靠的证据。本项目重点调查隐藏的无线设备的刺激和可观察的无线流量的结果模式之间的因果关系。本研究的目的是（一）设计实用的方法来查明无线隐藏设备利用人工刺激和由此产生的无线流量之间的相关性，以及（ii）制定对策，刺激响应为基础的设备定位方案。该项目将创建技术，充分保护用户隐私，防止通过无线隐藏设备进行未经授权的监控。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

When Free Tier Becomes Free to Enter: A Non-Intrusive Way to Identify Security Cameras with no Cloud Subscription

• DOI: 10.1145/3576915.3623083
• 发表时间: 2023-11
• 期刊: Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security
• 作者: Yan He;Qiuye He;Song Fang;Yao Liu

A Survey on Human Profile Information Inference via Wireless Signals

无线信号人体轮廓信息推断研究综述

• DOI: 10.1109/comst.2024.3373397
• 发表时间: 2024
• 期刊: IEEE Communications Surveys & Tutorials
• 影响因子: 35.6
• 作者: He, Qiuye;Yang, Edwin;Fang, Song
• 通讯作者: Fang, Song

Phantom-CSI Attacks against Wireless Liveness Detection

• DOI: 10.1145/3607199.3607245
• 发表时间: 2023-10
• 期刊: Proceedings of the 26th International Symposium on Research in Attacks, Intrusions and Defenses
• 作者: Qiuye He;Song Fang

Short: A data-driven respirator fit test model via human speech signal

• DOI: 10.1016/j.smhl.2023.100400
• 发表时间: 2023-03
• 期刊: Smart Health
• 作者: Jinmiao Chen;Zhaohe (John) Zhang;Shangqing Zhao;Song Fang;Thomas M. Peters;Evan L. Floyd;Changjie Cai-Chang

Precise Wireless Camera Localization Leveraging Traffic-Aided Spatial Analysis

• DOI: 10.1109/tmc.2023.3333272
• 发表时间: 2024-06
• 期刊: IEEE Transactions on Mobile Computing
• 影响因子: 7.9
• 作者: Yan He;Qiuye He;Song Fang;Yao Liu