Technical Report: Insider-Resistant Context-Based Pairing for Multimodality Sleep Apnea Test

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 a...

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Bibliographic Details
Published inarXiv.org
Main Authors Yao, Zheng, Shekh Md Mahmudul Islam, Pan, Yanjun, Millan, Marionne, Samson Aggelopoulos, Lu, Brian, Yang, Alvin, Yang, Thomas, Aelmore, Stephanie, Chang, Willy, Power, Alana, Li, Ming, Borić-Lubecke, Olga, Lubecke, Victor, Sun, Wenhai
Format Paper
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 24.05.2021
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Summary: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 prevents 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.
ISSN:2331-8422