Skip to main content
SpringerLink
Log in

Knowledge Discovery on Blockchains: Challenges and Opportunities for Distributed Event Detection Under Constraints

  • Conference paper
  • First Online:
ECML PKDD 2020 Workshops (ECML PKDD 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1323))

  • 2266 Accesses

Abstract

We study the applicability of blockchain technology for distributed event detection under resource constraints. Therefore we provide a test-suite with several promising consensus methods (Proof-of-Work, Proof-of-Stake, Distributed Proof-of-Work, and Practical Proof-of-Kernel-Work).

This is the first work analyzing the communication costs of blockchain consensus methods for knowledge discovery tasks in resource constraint devices. The experiments reveal that our proposed implementations of Distributed Proof-of-Work and Practical Proof-of-Kernel-Work provide a benefit over Proof-of-Work in CPU usage and communication costs. The tests show further that in cases of low data rates, where latencies by mining do not cause harm proposed blockchain implementations could be integrated. However, usage of blockchain requires data broadcasts, which leads to communication overhead as well as memory requirements based on the address list.

Supported by German Research Foundation DFG under grant SFB 876 “Providing Information by Resource-Constrained Data Analysis” project B4 “Analysis and Communication for Dynamic Traffic Prognosis”.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 79.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 99.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    https://opensensemap.org/.

  2. 2.

    Our sources and link to the data are available at https://bitbucket.org/cedric_sanders/abschlussarbeit/src/master/.

  3. 3.

    We are aware that by reduction of dimensionality collisions must occur, but as the hash function is hard to reverse also the collisions are hard to find.

  4. 4.

    Due to the strong connection to cryptocurrencies often named transactions.

  5. 5.

    The resulting sources are made publicly available at https://bitbucket.org/cedric_sanders/blockchain-experiments/src/master/.

  6. 6.

    https://opensensemap.org/.

  7. 7.

    https://opensensemap.org/.

  8. 8.

    The data we apply the method to is obtained in the interval from March, 23rd 2019 till March, 24th 2019, in the WGS 84 box [5.98865807458, 47.3024876979, 15.0169958839, 54.983104153].

References

  1. Buterin, V., et al.: A next-generation smart contract and decentralized application platform. White paper (2014)

    Google Scholar 

  2. CICADA: Cicada: a distributed direct democracy and decentralized appilcation platform. iamcicada.com/whitepaper/. Accessed 30 Mar 2019

  3. DML: Decentralized machine learning. https://decentralizedml.com/DML_whitepaper_31Dec_17.pdf. Accessed 02 Apr 2019

  4. Domingos, P., Hulten, G.: Mining high-speed data streams. In: KDD, vol. 2, p. 4 (2000)

    Google Scholar 

  5. Fayyad, U., Piatetsky-Shapiro, G., Smyth, P.: From data mining to knowledge discovery in databases. AI Mag. 17(3), 37 (1996)

    Google Scholar 

  6. Goldberg, S., Naor, M., Papadopoulos, D., Reyzin, L.: Nsec5 from elliptic curves: Provably preventing dnssec zone enumeration with shorter responses. IACR Cryptology ePrint Archive 2016, 83 (2016)

    Google Scholar 

  7. Griggs, K.N., Ossipova, O., Kohlios, C.P., Baccarini, A.N., Howson, E.A., Hayajneh, T.: Healthcare blockchain system using smart contracts for secure automated remote patient monitoring. J. Med. Syst. 42(7), 130 (2018)

    Article  Google Scholar 

  8. Kamp, M., et al.: Efficient decentralized deep learning by dynamic model averaging. In: Berlingerio, M., Bonchi, F., Gärtner, T., Hurley, N., Ifrim, G. (eds.) ECML PKDD 2018. LNCS (LNAI), vol. 11051, pp. 393–409. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-10925-7_24

    Chapter  Google Scholar 

  9. Keren, D., et al.: Geometric monitoring of heterogeneous streams. IEEE Trans. Knowl. Data Eng. 26(8), 1890–1903 (2014)

    Article  Google Scholar 

  10. King, S., Nadal, S.: Ppcoin: peer-to-peer crypto-currency with proof-of-stake. Self-published paper, 19 August 2012

    Google Scholar 

  11. Lazerson, A., Keren, D., Schuster, A.: Lightweight monitoring of distributed streams. ACM Trans. Database Syst. (TODS) 43(2), 9 (2018)

    Article  MathSciNet  Google Scholar 

  12. Lundbæk, L.N., Beutel, D.J., Huth, M., Kirk, L.: Practical proof of kernel work & distributed adaptiveness, manuscript Version 1.2 (2018)

    Google Scholar 

  13. May, M., Berendt, B., Cornue, A., et al.: Research challenges in ubiquitous knowledge discovery. In: Next Generation of Data Mining, pp. 154–173. Chapman and Hall/CRC (2008)

    Google Scholar 

  14. Micali, S., Rabin, M., Vadhan, S.: Verifiable random functions. In: 1999 40th Annual Symposium on Foundations of Computer Science, pp. 120–130. IEEE (1999)

    Google Scholar 

  15. Milutinovic, M., He, W., Wu, H., Kanwal, M.: Proof of luck: an efficient blockchain consensus protocol. In: Proceedings of the 1st Workshop on System Software for Trusted Execution, p. 2. ACM (2016)

    Google Scholar 

  16. Nakamoto, S.: Bitcoin: a peer-to-peer electronic cash system (2008)

    Google Scholar 

  17. P4Titan: Slimcoin: a peer-to-peer crypto-currency with proof-of-burn (2014)

    Google Scholar 

  18. PUB, F.: Secure hash standard (SHS). FIPS PUB 180(4) (2012)

    Google Scholar 

  19. Sharfman, I., Schuster, A., Keren, D.: A geometric approach to monitoring threshold functions over distributed data streams. ACM Trans. Database Syst. (TODS) 32(4), 23 (2007)

    Article  Google Scholar 

  20. Wolff, R., Bhaduri, K., Kargupta, H.: A generic local algorithm for mining data streams in large distributed systems. IEEE Trans. Knowl. Data Eng. 21(4), 465–478 (2009)

    Article  Google Scholar 

  21. Wood, G.: Ethereum: a secure decentralised generalised transaction ledger. Ethereum Proj. Yellow Paper 151, 1–32 (2014)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Artificial Intelligence Unit, TU Dortmund, 44269, Dortmund, Germany

    Cedric Sanders & Thomas Liebig

  2. Artificial Intelligence Unit, Universtiy of Nicosia, PO 24005, 1700, Nicosia, Cyprus

    Thomas Liebig

  3. Artificial Intelligence Unit, Materna Information and Communications SE, 44141, Dortmund, Germany

    Thomas Liebig

Authors
  1. Cedric Sanders
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Thomas Liebig
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Thomas Liebig .

Editor information

Editors and Affiliations

  1. University of Sydney, Sydney, NSW, Australia

    Irena Koprinska

  2. Monash University, Clayton, VIC, Australia

    Michael Kamp

  3. University of Bari Aldo Moro, Bari, Italy

    Annalisa Appice

  4. University of Bari Aldo Moro, Bari, Italy

    Corrado Loglisci

  5. University of Guelph, Guelph, ON, Canada

    Luiza Antonie

  6. University of Caen Normandy, Caen, France

    Albrecht Zimmermann

  7. University of Pisa, Pisa, Italy

    Riccardo Guidotti

  8. Norwegian University of Science and Technology, Trondheim, Norway

    Özlem Özgöbek

  9. University of Porto, Porto, Portugal

    Rita P. Ribeiro

  10. UPC BarcelonaTech, Barcelona, Spain

    Ricard Gavaldà

  11. University of Porto, Porto, Portugal

    João Gama

  12. Fraunhofer IAIS, St. Augustin, Germany

    Linara Adilova

  13. Royal Holloway University of London, Egham, UK

    Yamuna Krishnamurthy

  14. University of Lisbon, Lisbon, Portugal

    Pedro M. Ferreira

  15. University of Bari Aldo Moro, Bari, Italy

    Donato Malerba

  16. University of Lisbon, Lisbon, Portugal

    Ibéria Medeiros

  17. University of Bari Aldo Moro, Bari, Italy

    Michelangelo Ceci

  18. ICAR-CNR, Rende, Italy

    Giuseppe Manco

  19. University of Naples Federico II, Naples, Italy

    Elio Masciari

  20. University of North Carolina, Charlotte, NC, USA

    Zbigniew W. Ras

  21. Australian National University, Canberra, ACT, Australia

    Peter Christen

  22. Leibniz University Hannover, Hannover, Germany

    Eirini Ntoutsi

  23. Technical University of Dortmund, Dortmund, Germany

    Erich Schubert

  24. University of Southern Denmark, Odense, Denmark

    Arthur Zimek

  25. University of Pisa, Pisa, Italy

    Anna Monreale

  26. Warsaw University of Technology, Warsaw, Poland

    Przemyslaw Biecek

  27. ISTI-CNR, PISA, Italy

    Salvatore Rinzivillo

  28. Berlin Institute of Technology, Berlin, Germany

    Benjamin Kille

  29. Berlin Institute of Technology, Berlin, Germany

    Andreas Lommatzsch

  30. Norwegian University of Science and Technology, Trondheim, Norway

    Jon Atle Gulla

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Sanders, C., Liebig, T. (2020). Knowledge Discovery on Blockchains: Challenges and Opportunities for Distributed Event Detection Under Constraints. In: Koprinska, I., et al. ECML PKDD 2020 Workshops. ECML PKDD 2020. Communications in Computer and Information Science, vol 1323. Springer, Cham. https://doi.org/10.1007/978-3-030-65965-3_8

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-65965-3_8

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-65964-6

  • Online ISBN: 978-3-030-65965-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Societies and partnerships

Search

Navigation