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Filters: Author is Agrawal, Gagan  [Clear All Filters]
2022-01-31
Troyer, Dane, Henry, Justin, Maleki, Hoda, Dorai, Gokila, Sumner, Bethany, Agrawal, Gagan, Ingram, Jon.  2021.  Privacy-Preserving Framework to Facilitate Shared Data Access for Wearable Devices. 2021 IEEE International Conference on Big Data (Big Data). :2583—2592.
Wearable devices are emerging as effective modalities for the collection of individuals’ data. While this data can be leveraged for use in several areas ranging from health-care to crime investigation, storing and securely accessing such information while preserving privacy and detecting any tampering attempts are significant challenges. This paper describes a decentralized system that ensures an individual’s privacy, maintains an immutable log of any data access, and provides decentralized access control management. Our proposed framework uses a custom permissioned blockchain protocol to securely log data transactions from wearable devices in the blockchain ledger. We have implemented a proof-of-concept for our framework, and our preliminary evaluation is summarized to demonstrate our proposed framework’s capabilities. We have also discussed various application scenarios of our privacy-preserving model using blockchain and proof-of-authority. Our research aims to detect data tampering attempts in data sharing scenarios using a thorough transaction log model.