Data Provenance Assurance for Cloud Storage Using Blockchain
Title | Data Provenance Assurance for Cloud Storage Using Blockchain |
Publication Type | Conference Paper |
Year of Publication | 2020 |
Authors | Patil, A., Jha, A., Mulla, M. M., Narayan, D. G., Kengond, S. |
Conference Name | 2020 International Conference on Advances in Computing, Communication Materials (ICACCM) |
Date Published | Aug. 2020 |
Publisher | IEEE |
ISBN Number | 978-1-7281-9785-2 |
Keywords | AWS S3, AWS S3 storage, blockchain network, cloud computing, cloud data object, cloud forensics, cloud infrastructures, cloud storage, cloud storage forensics, cloud-based data provenance, composability, confidential files, contracts, cryptography, data accountability, data integrity, data privacy, data provenance assurance, Data Provenances, data record operations, digital forensics, Distributed databases, ethereum, Ethereum blockchain, Forensics, IPFS, metadata, Metrics, network accountability, privacy, pubcrawl, resilience, Resiliency, SLA-violations, storage management, storage privacy |
Abstract | Cloud forensics investigates the crime committed over cloud infrastructures like SLA-violations and storage privacy. Cloud storage forensics is the process of recording the history of the creation and operations performed on a cloud data object and investing it. Secure data provenance in the Cloud is crucial for data accountability, forensics, and privacy. Towards this, we present a Cloud-based data provenance framework using Blockchain, which traces data record operations and generates provenance data. Initially, we design a dropbox like application using AWS S3 storage. The application creates a cloud storage application for the students and faculty of the university, thereby making the storage and sharing of work and resources efficient. Later, we design a data provenance mechanism for confidential files of users using Ethereum blockchain. We also evaluate the proposed system using performance parameters like query and transaction latency by varying the load and number of nodes of the blockchain network. |
URL | https://ieeexplore.ieee.org/document/9213032 |
DOI | 10.1109/ICACCM50413.2020.9213032 |
Citation Key | patil_data_2020 |
- Metrics
- data record operations
- Digital Forensics
- Distributed databases
- ethereum
- Ethereum blockchain
- Forensics
- IPFS
- metadata
- Data Provenances
- network accountability
- privacy
- pubcrawl
- resilience
- Resiliency
- SLA-violations
- storage management
- storage privacy
- cloud-based data provenance
- AWS S3 storage
- blockchain network
- Cloud Computing
- cloud data object
- cloud forensics
- cloud infrastructures
- cloud storage
- cloud storage forensics
- AWS S3
- composability
- confidential files
- contracts
- Cryptography
- data accountability
- data integrity
- data privacy
- data provenance assurance