Long Transaction Chains and the Bitcoin Heartbeat

  • Giuseppe Di BattistaEmail author
  • Valentino Di Donato
  • Maurizio Pizzonia
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10659)


Over the past few years a persistent growth of the number of daily Bitcoin transactions has been observed. This trend however, is known to be influenced by a number of phenomena that generate long transaction chains that are not related to real purchases (e.g. wallets shuffling and coin mixing). For a transaction chain we call transaction chain frequency the number of transactions of the chain divided by the time interval of the chain. In this paper, we first analyze to which extent Bitcoin transactions are involved in high frequency transaction chains, in the short and in the long term. Based on this analysis, we then argue that a large fraction of transactions do not refer to explicit human activity, namely to transactions between users that trade goods or services. Finally, we show that most of the transactions are involved into chains whose frequency is roughly stable over time and that we call Bitcoin Heartbeat.


Bitcoin Cryptocurrency Transaction graph 


  1. 1.
  2. 2.
  3. 3.
    Evolution of the number of bitcoin transactions.
  4. 4.
    Bonneau, J., Miller, A., Clark, J., Narayanan, A., Kroll, J.A., Felten, E.W.: SoK: research perspectives and challenges for bitcoin and cryptocurrencies. In: 2015 IEEE Symposium on Security and Privacy, pp. 104–121, May 2015Google Scholar
  5. 5.
    Di Battista, G., Di Donato, V., Patrignani, M., Pizzonia, M., Roselli, V., Tamassia, R.: Bitconeview: visualization of flows in the bitcoin transaction graph. In: 2015 IEEE Symposium on Visualization for Cyber Security (VizSec), pp. 1–8 (2015)Google Scholar
  6. 6.
    Di Francesco Maesa, D., Marino, A., Ricci, L.: Uncovering the Bitcoin Blockchain: an analysis of the full users graph. In: 2016 IEEE International Conference on Data Science and Advanced Analytics (DSAA), pp. 537–546, October 2016Google Scholar
  7. 7.
    Di Francesco Maesa, D., Marino, A., Ricci, L.: Data-driven analysis of bitcoin properties: exploiting the users graph. Int. J. Data Sci. Anal. (2017).
  8. 8.
    Fabrikant, A., Koutsoupias, E., Papadimitriou, C.H.: Heuristically optimized trade-offs: a new paradigm for power laws in the internet. In: Widmayer, P., Eidenbenz, S., Triguero, F., Morales, R., Conejo, R., Hennessy, M. (eds.) ICALP 2002. LNCS, vol. 2380, pp. 110–122. Springer, Heidelberg (2002). CrossRefGoogle Scholar
  9. 9.
    McGinn, D., Birch, D., Akroyd, D., Molina-Solana, M., Guo, Y., Knottenbelt, W.: Visualizing dynamic bitcoin transaction patterns. Big Data
  10. 10.
    Meiklejohn, S., Pomarole, M., Jordan, G., Levchenko, K., McCoy, D., Voelker, G.M., Savage, S.: A fistful of bitcoins: characterizing payments among men with no names. In: Proceedings of the ACM Internet Measurement Conference, IMC, pp. 127–140 (2013)Google Scholar
  11. 11.
    Nakamoto, S.: Bitcoin: a peer-to-peer electronic cash system (2008).
  12. 12.
    Ober, M., Katzenbeisser, S., Hamacher, K.: Structure and anonymity of the bitcoin transaction graph. Future Internet 5(2), 237–250 (2013). CrossRefGoogle Scholar
  13. 13.
    Reid, F., Harrigan, M.: An analysis of anonymity in the bitcoin system. In: 2011 IEEE Third International Conference on Privacy, Security, Risk and Trust and 2011 IEEE Third International Conference on Social Computing, pp. 1318–1326, October 2011Google Scholar
  14. 14.
    Ron, D., Shamir, A.: Quantitative analysis of the full bitcoin transaction graph. In: Sadeghi, A.-R. (ed.) FC 2013. LNCS, vol. 7859, pp. 6–24. Springer, Heidelberg (2013). CrossRefGoogle Scholar
  15. 15.
    Skiena, S.S.: The Algorithm Design Manual, 2nd edn. Springer Publishing Company, Incorporated, London (2008). CrossRefzbMATHGoogle Scholar
  16. 16.
    Yli-Huumo, J., Ko, D., Choi, S., Park, S., Smolander, K.: Where is current research on blockchain technology?—a systematic review. PLoS One 11(10), 1–27 (2016)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of EngineeringRoma Tre UniversityRomeItaly

Personalised recommendations