short-paper

Public Access

SmartProvenance: A Distributed, Blockchain Based DataProvenance System

Authors:

Aravind Ramachandran and

Murat KantarciogluAuthors Info & Claims

CODASPY '18: Proceedings of the Eighth ACM Conference on Data and Application Security and Privacy

March 2018

Pages 35 - 42

https://doi.org/10.1145/3176258.3176333

Published: 13 March 2018 Publication History

Abstract

Blockchain technology has evolved from being an immutable ledger of transactions for cryptocurrencies to a programmable interactive environment for building distributed reliable applications. Although the blockchain technology has been used to address various challenges, to our knowledge none of the previous work focused on using Blockchain to develop a secure and immutable scientific data provenance management framework that automatically verifies the provenance records. In this work, we leverage Blockchain as a platform to facilitate trustworthy data provenance collection, verification, and management. The developed system utilizes smart contracts and open provenance model (OPM) to record immutable data trails. We show that our proposed framework can securely capture and validate provenance data that prevents any malicious modification to the captured data as long as the majority of the participants are honest.

References

[1]

Thiago Vieira Andrew Lippman Ariel Ekblaw, Asaf Azaria. 2016. MedRec: Medical Data Management on the Blockchain. (2016). version: 57e013615dbf3f3300152554.

[2]

David Bollier. 2015. Reinventing Law for the Commons. (2015). http://www. commonaccord.org/

[3]

Zvika Brakerski, Jonathan Katz, Gil Segev, and Arkady Yerukhimovich. 2011. Limits on the Power of Zero-Knowledge Proofs in Cryptographic Constructions. In Theory of Cryptography - 8th Theory of Cryptography Conference, TCC 2011, Providence, RI, USA, March 28-30, 2011. Proceedings. 559--578.

Digital Library

[4]

Jonathan Brown. 2015. Storing compressed text in Ethereum transaction logs. (2015). http://jonathanpatrick.me/blog/ethereum-compressed-text

[5]

Vitalik Buterin. 2015. A Next-Generation Smart Contract and Decentralized Application Platform. (2015). September.

[6]

Tim Clark, Paolo Ciccarese, and Carole A. Goble. 2013. Micropublications: a Semantic Model for Claims, Evidence, Arguments and Annotations in Biomedical Communications. CoRR abs/1305.3506 (2013). http://arxiv.org/abs/1305.3506

[7]

Tierion coporation. 2017. Tierion API. (2017). https://tierion.com/

[8]

Vincent Durham. 2010. NAMECOIN. https://namecoin.org/.

[9]

The Economist. 2016. Better with bitcoin. (2016). http://www.economist.com/news/science-and-technology/21699099- blockchain-technology-could-improve-reliability-medical-trials-better.

[10]

US Food and Drug Administration. 2017. Clinical Research. https://www.fda.gov/ ForPatients/Approvals/Drugs/ucm405622.htm.

[11]

Buyse M George SL. 2015. Data fraud in clinical trials. PMC 5, 2 (2015), 161--173.

[12]

Bela Gipp, Jagrut Kosti, and Corinna Breitinger. 2016. Securing Video Integrity Using Decentralized Trusted Timestamping on the Blockchain. In Proceedings of the 10th Mediterranean Conference on Information Systems (MCIS). Paphos, Cyprus.

[13]

Oded Goldreich. 2004. Foundations of Cryptography: Volume 2, Basic Applications. Cambridge University Press, New York, NY, USA.

Digital Library

[14]

Google. 2017. Google Appscript. https://developers.google.com/apps-script/.

[15]

Gideon Greenspan. 2016. Four Genuine Blockchain Use Cases. (May 2016). http://www.coindesk.com/four-genuine-blockchain-use-cases/

[16]

R. R. Downs R. Duerr J. C. Goldstein M. A. Parsons Hills, D. J. and H. K. Ramapriyan. 2015. The importance of data set provenance for science. (2015). version:

[17]

Roman JagomÃdgis, Peeter Laud, and Alisa Pankova. 2015. Preprocessing-Based Verification of Multiparty Protocols with Honest Majority. Cryptology ePrint Archive, Report 2015/674. (2015). http://eprint.iacr.org/2015/674.

[18]

Cruz Jason, Paul and Kaji Yuichi. 2015. The Bitcoin Network as Platform for Trans-Organizational Attribute Authentication. IPSJ SIG Notes 2015, 12 (feb 2015), 1--6. http://ci.nii.ac.jp/naid/110009877764/en/

[19]

Ahmed Kosba Andrew Miller Kevin Delmolino, Mitchell Arnett and Elaine Shi. 2015. Step by Step Towards Creating a Safe Smart Contract: Lessons and Insights from a Cryptocurrency Lab. Cryptology ePrint Archive, Report 2015/460. (2015). http://eprint.iacr.org/2015/460.

[20]

Ahmed Kosba, Andrew Miller, Elaine Shi, Zikai Wen, and Charalampos Papa- manthou. 2015. Hawk: The Blockchain Model of Cryptography and Privacy-Preserving Smart Contracts. Cryptology ePrint Archive, Report 2015/675. (2015). http://eprint.iacr.org/2015/675.

[21]

Xueping Liang, Sachin Shetty, Deepak Tosh, Charles Kamhoua, Kevin Kwiat, and Laurent Njilla. 2017. ProvChain: A Blockchain-based Data Provenance Architecture in Cloud Environment with Enhanced Privacy and Availability. In Proceedings of the 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid '17). IEEE Press, Piscataway, NJ, USA, 468--477.

Digital Library

[22]

Peter Linder. 2016. DEcryption Contract ENforcement Tool (DECENT): A Practical Alternative to Government Decryption Backdoors. Cryptology ePrint Archive, Report 2016/245. (2016). http://eprint.iacr.org/2016/245.

[23]

Project Provenance Ltd. 2015. Blockchain: the solution for transparency in product supply chains. (2015). https://www.provenance.org/whitepaper

[24]

MeteorJs. 2016. (May 2016). https://www.meteor.com/

[25]

MongoDB. 2017. MongoDB. (Jan. 2017). https://www.mongodb.com/

[26]

Open Provenance model 2007. Open Provenance Model. Open Provenance model. http://openprovenance.org/.

[27]

Aafaf Ouaddah, Anas Abou El Kalam, and Abdellah Ait Ouahman. 2016. FairAccess: a new Blockchain-based access control framework for the Internet of Things. Security and Communication Networks 9, 18 (2016), 5943--5964.

[28]

Eric F. Pettersen, Thomas D. Goddard, Conrad C. Huang, Gregory S. Couch, Daniel M. Greenblatt, Elaine C. Meng, and Thomas E. Ferrin. 2004. UCSF Chimera - A visualization system for exploratory research and analysis. Journal of Computational Chemistry 25, 13 (2004), 1605--1612.

[29]

Aravind Ramachandran and Murat Kantarcioglu. 2017. Using Blockchain and smart contracts for secure data provenance management. (2017). https://arxiv.org/abs/1709.10000

[30]

Gavin Wood. 2017. ETHEREUM: A secure decentralized generalized transaction ledger. (2017). http://gavwood.com/paper.pdf

Cited By

Umer MBelay EGouveia L(2024)Leveraging Artificial Intelligence and Provenance Blockchain Framework to Mitigate Risks in Cloud Manufacturing in Industry 4.0Electronics10.3390/electronics1303066013:3(660)Online publication date: 5-Feb-2024
https://doi.org/10.3390/electronics13030660
Mertens DKim JXu JKim ELee C(2024)Smart flow: a provenance-supported smart contract workflow architectureCluster Computing10.1007/s10586-024-04390-xOnline publication date: 8-Apr-2024
https://doi.org/10.1007/s10586-024-04390-x
Ogundokun RArowolo MDamaševičius RMisra S(2023)Phishing Detection in Blockchain Transaction Networks Using Ensemble LearningTelecom10.3390/telecom40200174:2(279-297)Online publication date: 31-May-2023
https://doi.org/10.3390/telecom4020017
Show More Cited By

Index Terms

SmartProvenance: A Distributed, Blockchain Based DataProvenance System
1. Information systems
  1. Data management systems
    1. Database design and models
      1. Data model extensions
        Data provenance
2. Theory of computation
  1. Theory and algorithms for application domains
    1. Database theory
      1. Data provenance

Recommendations

Toward the modeling of data provenance in scientific publications

In this paper, we implement a provenance-aware system for documenting publications, called PADS. It employs a three-layered provenance hierarchy, which can output diverse types of provenance data related to the research life cycle. From this, we ...
Read More
ProvChain: A Blockchain-based Data Provenance Architecture in Cloud Environment with Enhanced Privacy and Availability
CCGrid '17: Proceedings of the 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing

Cloud data provenance is metadata that records the history of the creation and operations performed on a cloud data object. Secure data provenance is crucial for data accountability, forensics and privacy. In this paper, we propose a decentralized and ...
Read More
Why blockchain needs graph: A survey on studies, scenarios, and solutions
Abstract
The popularity of blockchain platforms and their applications in industry and academia keeps rising. The multifarious requirements stimulate another technique, graph data and algorithms, to join the blockchains; thus, studies, ...
Highlights
- Summarize and classify prior works on existing graph-related blockchains.
- ...
Read More

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

CODASPY '18: Proceedings of the Eighth ACM Conference on Data and Application Security and Privacy

March 2018

401 pages

ISBN:9781450356329

DOI:10.1145/3176258

General Chairs:
Ziming Zhao
Arizona State University, USA
,
Gail-Joon Ahn
Arizona State University, USA & Samsung Research, Korea
,
Program Chairs:
Ram Krishnan
University of Texas at San Antonio, USA
,
Gabriel Ghinita
University of Massachusetts Boston, USA

Copyright © 2018 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

Sponsors

SIGSAC: ACM Special Interest Group on Security, Audit, and Control

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 13 March 2018

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Short-paper

Funding Sources

NIH
ARO
NSF

Conference

CODASPY '18

Sponsor:

SIGSAC

CODASPY '18: Eighth ACM Conference on Data and Application Security and Privacy

March 19 - 21, 2018

AZ, Tempe, USA

Acceptance Rates

CODASPY '18 Paper Acceptance Rate 23 of 110 submissions, 21%;

Overall Acceptance Rate 149 of 789 submissions, 19%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

50
Total Citations
View Citations
1,502
Total Downloads

Downloads (Last 12 months)168
Downloads (Last 6 weeks)18

Other Metrics

View Author Metrics

Citations

Cited By

Umer MBelay EGouveia L(2024)Leveraging Artificial Intelligence and Provenance Blockchain Framework to Mitigate Risks in Cloud Manufacturing in Industry 4.0Electronics10.3390/electronics1303066013:3(660)Online publication date: 5-Feb-2024
https://doi.org/10.3390/electronics13030660
Mertens DKim JXu JKim ELee C(2024)Smart flow: a provenance-supported smart contract workflow architectureCluster Computing10.1007/s10586-024-04390-xOnline publication date: 8-Apr-2024
https://doi.org/10.1007/s10586-024-04390-x
Ogundokun RArowolo MDamaševičius RMisra S(2023)Phishing Detection in Blockchain Transaction Networks Using Ensemble LearningTelecom10.3390/telecom40200174:2(279-297)Online publication date: 31-May-2023
https://doi.org/10.3390/telecom4020017
Akbarfam AHeidaripour MMaleki HDorai GAgrawal G(2023)ForensiBlock: A Provenance-Driven Blockchain Framework for Data Forensics and Auditability2023 5th IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA)10.1109/TPS-ISA58951.2023.00025(136-145)Online publication date: 1-Nov-2023
https://doi.org/10.1109/TPS-ISA58951.2023.00025
Zhang YZhao JJiang JZhu YWang LXiang Y(2023)Recording Behaviors of Artificial Intelligence in BlockchainsIEEE Transactions on Artificial Intelligence10.1109/TAI.2022.32135314:6(1437-1448)Online publication date: Dec-2023
https://doi.org/10.1109/TAI.2022.3213531
Al-Mamun AZhao D(2023)ECHAIN: Securing Electronic Device Provenance through Privacy-Preserving Consortium Blockchains2023 53rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks - Supplemental Volume (DSN-S)10.1109/DSN-S58398.2023.00028(77-83)Online publication date: Jun-2023
https://doi.org/10.1109/DSN-S58398.2023.00028
Kiourtis AMavrogiorgou AMakridis GFatouros GSoldatos JKyriazis D(2023)Data Marketplaces: Best Practices, Challenges, and Advancements for Embedded Finance2023 19th International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT)10.1109/DCOSS-IoT58021.2023.00088(533-540)Online publication date: Jun-2023
https://doi.org/10.1109/DCOSS-IoT58021.2023.00088
Sun LZhou DLiu DTang JLi Y(2023)BPDAC: A Blockchain Based and Provenance Enabled Dynamic Access Control SchemeIEEE Access10.1109/ACCESS.2023.334088711(142552-142568)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3340887
Costa‐Pérez XSciancalepore VZanzi LAlbanese A(2023)Blockchain for Mobile NetworksBlockchains10.1002/9781119781042.ch7(185-213)Online publication date: 8-Sep-2023
https://doi.org/10.1002/9781119781042.ch7
Kuftinova NMaksimychev OOstroukh AVolosova AMatukhina E(2022)Data Fabric as an Effective Method of Data Management in Traffic and Road Systems2022 Systems of Signals Generating and Processing in the Field of on Board Communications10.1109/IEEECONF53456.2022.9744402(1-4)Online publication date: 15-Mar-2022
https://doi.org/10.1109/IEEECONF53456.2022.9744402
Show More Cited By

View Options

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

Media

Figures

Other

Tables

View Table of Contents