Insider-Resistant Context-Based Pairing for Multimodality Sleep Apnea Test

Yao Zheng, Shekh Md Mahmudul Islam, Yanjun Pan, Marionne Millan, Samson Aggelopoulos, Brian Lu, Alvin Yang, Thomas Yang, Stephanie Aelmore, Willy Chang, Alana Power, Ming Li, Olga Boric-Lubecke, Victor Lubecke, Wenhai Sun

Research output: Contribution to journalConference articlepeer-review

1 Scopus citations


The increasingly sophisticated at-home screening systems for obstructive sleep apnea (OSA), integrated with both contactless and contact-based sensing modalities, bring convenience and reliability to remote chronic disease management. However, the device pairing processes between system components are vulnerable to wireless exploitation from a non-compliant user wishing to manipulate the test results. This work presents SIENNA, an insider-resistant context-based pairing protocol. SIENNA leverages JADE-ICA to uniquely identify a user's respiration pattern within a multi-person environment and fuzzy commitment for automatic device pairing, while using friendly jamming technique to prevent an insider with knowledge of respiration patterns from acquiring the pairing key. Our analysis and test results show that SIENNA can achieve reliable (> 90% success rate) device pairing under a noisy environment and is robust against the attacker with full knowledge of the context information.

Original languageEnglish (US)
JournalProceedings - IEEE Global Communications Conference, GLOBECOM
StatePublished - 2021
Event2021 IEEE Global Communications Conference, GLOBECOM 2021 - Madrid, Spain
Duration: Dec 7 2021Dec 11 2021

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Hardware and Architecture
  • Signal Processing


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