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.

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.

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