Nowhere to Hide: Cross-Modal Identity Leakage between Biometrics and Devices

Chris Xiaoxuan Lu, Yang Li, Yuanbo Xiangli, Zhengxiong Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Along with the benefits of Internet of Things (IoT) come potential privacy risks, since billions of the connected devices are granted permission to track information about their users and communicate it to other parties over the Internet. Of particular interest to the adversary is the user identity which constantly plays an important role in launching attacks. While the exposure of a certain type of physical biometrics or device identity is extensively studied, the compound effect of leakage from both sides remains unknown in multi-modal sensing environments. In this work, we explore the feasibility of the compound identity leakage across cyber-physical spaces and unveil that co-located smart device IDs (e.g., smartphone MAC addresses) and physical biometrics (e.g., facial/vocal samples) are side channels to each other. It is demonstrated that our method is robust to various observation noise in the wild and an attacker can comprehensively profile victims in multi-dimension with nearly zero analysis effort. Two real-world experiments on different biometrics and device IDs show that the presented approach can compromise more than 70% of device IDs and harvests multiple biometric clusters with purity at the same time.
Original languageEnglish
Title of host publicationProceedings of The Web Conference 2020
Place of PublicationNew York, NY, USA
PublisherACM Association for Computing Machinery
ISBN (Print)9781450370233
Publication statusPublished - 20 Apr 2020
EventThe Web Conference 2020 - Taipei, Taiwan, Province of China
Duration: 20 Apr 202024 Apr 2020

Publication series

NameWWW '20
PublisherAssociation for Computing Machinery


ConferenceThe Web Conference 2020
Abbreviated titleWWW 2020
Country/TerritoryTaiwan, Province of China
Internet address


  • Internet of Things
  • Cross-modality Association
  • Identity Leakage


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