Biblio
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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.
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2020. Analysis of iOS SQLite Schema Evolution for Updating Forensic Data Extraction Tools. 2020 8th International Symposium on Digital Forensics and Security (ISDFS). :1—7.
Files in the backup of iOS devices can be a potential source of evidentiary data. Particularly, the iOS backup (obtained through a logical acquisition technique) is widely used by many forensic tools to sift through the data. A significant challenge faced by several forensic tool developers is the changes in the data organization of the iOS backup. This is due to the fact that the iOS operating system is frequently updated by Apple Inc. Many iOS application developers release periodical updates to iOS mobile applications. Both these reasons can cause significant changes in the way user data gets stored in the iOS backup files. Moreover, approximately once every couple years, there could be a major iOS release which can cause the reorganization of files and folders in the iOS backup. Directories in the iOS backup contain SQLite databases, plist files, XML files, text files, and media files. Android/iOS devices generally use SQLite databases since it is a lightweight database. Our focus in this paper is to analyze the SQLite schema evolution specific to iOS and assist forensic tool developers in keeping their tools compatible with the latest iOS version. Our recommendations for updating the forensic data extraction tools is based on the observation of schema changes found in successive iOS versions.