Visible to the public Secure Lightweight Context-Driven Data Logging for Bodyworn Sensing Devices

TitleSecure Lightweight Context-Driven Data Logging for Bodyworn Sensing Devices
Publication TypeConference Paper
Year of Publication2017
AuthorsSiddiqi, M., All, S. T., Sivaraman, V.
Conference Name2017 5th International Symposium on Digital Forensic and Security (ISDFS)
Date Publishedapr
KeywordsBiomedical monitoring, blockchain, Bloom filters, body sensor networks, bodyworn sensing devices, chronological epoch-level blocks, contextual information security, data fingerprint storage, data handling, data structures, digital forensics, Forensics, Human Behavior, localization, Logic gates, medical computing, Medical diagnostic imaging, medical domain, Medical services, Monitoring, privacy, pubcrawl, recording, resilience, Resiliency, Scalability, secure lightweight context-driven data logging, sensor medical data storage, sensor placement, Sensors, timestamping, wearable technology, wearables security

Rapid advancement in wearable technology has unlocked a tremendous potential of its applications in the medical domain. Among the challenges in making the technology more useful for medical purposes is the lack of confidence in the data thus generated and communicated. Incentives have led to attacks on such systems. We propose a novel lightweight scheme to securely log the data from bodyworn sensing devices by utilizing neighboring devices as witnesses who store the fingerprints of data in Bloom filters to be later used for forensics. Medical data from each sensor is stored at various locations of the system in chronological epoch-level blocks chained together, similar to the blockchain. Besides secure logging, the scheme offers to secure other contextual information such as localization and timestamping. We prove the effectiveness of the scheme through experimental results. We define performance parameters of our scheme and quantify their cost benefit trade-offs through simulation.

Citation Keysiddiqi_secure_2017