Advertisement

Scrybe: A Second-Generation Blockchain Technology with Lightweight Mining for Secure Provenance and Related Applications

  • Carl Worley
  • Lu Yu
  • Richard Brooks
  • Jon Oakley
  • Anthony Skjellum
  • Amani Altarawneh
  • Sai MeduryEmail author
  • Ujan Mukhopadhyay
Chapter
  • 92 Downloads
Part of the Advances in Information Security book series (ADIS, volume 79)

Abstract

The recent popularity of cryptocurrencies has highlighted the versatility and applications of a decentralized, public blockchain. Blockchain provides a data structure that can guarantee both the integrity and non-repudiation of data, as well as providing provenance pertaining to such data. Our novel Lightweight Mining (LWM) algorithm provides these guarantees with minimal resource requirements. Our approach to blockchain-based data provenance, paired with the LWM algorithm, provides the legal and ethical framework for key classes of provenance to be managed. Contributions of this paper include the following: first, we describe the Scrybe system, including the Lightweight mining algorithm. We then note principles of secure provenance and explain how to adapt Scrybe to a series of practical use cases, such as academic integrity, forensic management of evidence, and secure logging. Finally, we explain the key features of the Scrybe system that enable secure provenance for these use cases, and we describe resilience of the system to denial of service attacks and repudiation.

Notes

Acknowledgements

This material is based upon work supported by the National Science Foundation under Grant Nos. 1547164, 1547245, 1049765, and 1821926, and by the NIH National Center for Advancing Translational Sciences (NCATS) through Grant No. UL1 TR001450. Any opinions, findings, conclusions, or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation or the National Institutes of Health.

References

  1. 1.
    V. Vishnumurthy, S. Chandrakumar, E.G. Sirer, Karma: a secure economic framework for peer-to-peer resource sharing, in Workshop on Economics of Peer-to-peer Systems, vol. 35, 2003Google Scholar
  2. 2.
    R. Brooks, A. Skjellum, Using the blockchain to secure provenance meta-data (a CCoE webinar presentation) (2017)Google Scholar
  3. 3.
    U. Mukhopadhyay, A. Skjellum, O. Hambolu, J. Oakley, L. Yu, R. Brooks, A brief survey of cryptocurrency systems, in 2016 14th Annual Conference on Privacy, Security and Trust (PST) (IEEE, New York, 2016), pp. 745–752CrossRefGoogle Scholar
  4. 4.
    Technopedia, Data lineage. Online. Accessed 27 Feb 2018Google Scholar
  5. 5.
    M. Benchoufi, R. Porcher, P. Ravaud, Blockchain protocols in clinical trials: transparency and traceability of consent, F1000Research 6 (2017)Google Scholar
  6. 6.
    M. Benchoufi, R. Porcher, P. Ravaud, Traceability of consent [version 3; referees: 1 approved, 2]Google Scholar
  7. 7.
    X. Liang, S. Shetty, D. Tosh, C. Kamhoua, K. Kwiat, L. Njilla, Provchain: a blockchain-based data provenance architecture in cloud environment with enhanced privacy and availability, in 2017 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID) (2017), pp. 468–477.  https://doi.org/10.1109/CCGRID.2017.8
  8. 8.
    Project Provenance Ltd., Blockchain: the solution for transparency in product supply chains (2015). https://www.provenance.org/whitepaper. Accessed 15 Aug 2018
  9. 9.
    A. Benningfield, Hyperledger - supply chain traceability: anti counterfeiting (2015). https://docs.google.com/document/d/1V0WpEggrHrBNaCL_gQrynqqmFaT3cNQw6hj1AhfkTPk/edit. Accessed 15 Aug 2018Google Scholar
  10. 10.
    B. Awerbuch, C. Scheideler, Robust random number generation for peer-to-peer systems. Theor. Comput. Sci. 410, 453–466 (2006)MathSciNetCrossRefGoogle Scholar
  11. 11.
    S. Nakamoto, Bitcoin: a peer-to-peer electronic cash system (2008)Google Scholar
  12. 12.
    Anonymous, Git. https://en.wikipedia.org/wiki/Git. Last Retrieved: 16 Mar 2018
  13. 13.
  14. 14.
    Anonymous, Nagios: The industry standard in IT infrastructure monitoring. https://www.nagios.org/. Last Retrieved: 16 Mar 2018
  15. 15.
    S. Medury, A. Skjellum, R. Brooks, L. Yu, SCRaaPS: X. 509 certificate revocation using the Blockchain-based Scrybe secure provenance system, in 2018 13th International Conference on Malicious and Unwanted Software (MALWARE) (IEEE, 2018), pp. 145–152Google Scholar
  16. 16.
    U. Guin, P. Cui, A. Skjellum, Ensuring Proof-of-Authenticity of IoT edge devices using Blockchain technology, in 2018 IEEE International Conference on Internet of Things, Green Computing and Communications, Cyber, Physical and Social Computing, Smart Data, Blockchain, Computer and Information Technology, Congress on Cybermatics (2018), pp. 1042–1050Google Scholar
  17. 17.
    O. Hambolu, L. Yu, J. Oakley, R.R. Brooks, U. Mukhopadhyay, A. Skjellum, Provenance threat modeling, in 2016 14th Annual Conference on Privacy, Security and Trust (PST) (IEEE, New York, 2016), pp. 384–387CrossRefGoogle Scholar
  18. 18.
    P. Ryan, S.A. Schneider, M. Goldsmith, G. Lowe, The Modelling and Analysis of Security Protocols: The CSP Approach (Addison-Wesley Professional, Boston, 2001)Google Scholar
  19. 19.
    K. Salimifard, M. Wright, Petri net-based modelling of workflow systems: an overview. Eur. J. Oper. Res. 134(3), 664–676 (2001)CrossRefGoogle Scholar
  20. 20.
    C.A.R. Hoare, Communicating sequential processes. Commun. ACM 21(8), 666–677 (1978)CrossRefGoogle Scholar
  21. 21.
    R. David, H. Alla, Petri Nets and Grafcet: Tools for Modelling Discrete Event Systems (Prentice Hall, New York, 1992)zbMATHGoogle Scholar
  22. 22.
    L. Yu, J.M. Schwier, R.M. Craven, R.R. Brooks, C. Griffin, Inferring statistically significant hidden Markov models. IEEE Trans. Knowl. Data Eng. 25(7), 1548–1558 (2013)CrossRefGoogle Scholar
  23. 23.
    Bitcoin Wiki, Proof of work (2014). https://en.bitcoin.it/wiki/Proof_of_work Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Carl Worley
    • 1
  • Lu Yu
    • 2
  • Richard Brooks
    • 2
  • Jon Oakley
    • 2
  • Anthony Skjellum
    • 3
  • Amani Altarawneh
    • 3
  • Sai Medury
    • 3
    Email author
  • Ujan Mukhopadhyay
    • 1
  1. 1.Department of Computer Science and Software EngineeringAuburn UniversityAuburnUSA
  2. 2.Department of Electrical and Computer EngineeringClemson UniversityClemsonUSA
  3. 3.SimCenter & Department of Computer Science and EngineeringUniversity of Tennessee at ChattanoogaChattanoogaUSA

Personalised recommendations