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Analyzing Ethereum's Contract Topology

Published:31 October 2018Publication History

ABSTRACT

Ethereum is the second most valuable cryptocurrency today, with a current market cap of over $68B. What sets Ethereum apart from other cryptocurrencies is that it uses the blockchain to not only store a record of transactions, but also smart contracts and a history of calls made to those contracts. Thus, Ethereum represents a new form of distributed system: one where users can implement contracts that can provide functionality such as voting protocols, crowdfunding projects, betting agreements, and many more. However, despite the massive investment, little is known about how contracts in Ethereum are actually created and used.

In this paper, we examine how contracts in Ethereum are created, and how users and contracts interact with one another. We modify the geth client to log all such interactions, and find that contracts today are three times more likely to be created by other contracts than they are by users, and that over 60% of contracts have never been interacted with. Additionally, we obtain the bytecode of all contracts and look for similarity; we find that less than 10% of user-created contracts are unique, and less than 1% of contract-created contracts are so. Clustering the contracts based on code similarity reveals even further similarity. These results indicate that there is substantial code re-use in Ethereum, suggesting that bugs in such contracts could have wide-spread impact on the Ethereum user population.

References

  1. Another parity wallet hack explained. https://medium.com/@Pr0Ger/another-parity-wallet-hack-explained-847ca46a2e1c.Google ScholarGoogle Scholar
  2. Spurious dragon hard fork. https://blog.ethereum.org/2016/11/18/hard-fork-no-4-spurious-dragon/, November 2016.Google ScholarGoogle Scholar
  3. Tangerine whistle. https://blog.ethereum.org/2016/10/18/faq-upcoming-ethereum-hard-fork/, October 2016.Google ScholarGoogle Scholar
  4. Cryptokitties craze slows down transactions on ethereum. http://www.bbc.com/news/technology-42237162, December 2017.Google ScholarGoogle Scholar
  5. L. Anderson, R. Holz, A. Ponomarev, P. Rimba, and I. Weber. New kids on the block: an analysis of modern blockchains. arXiv preprint arXiv:1606.06530, 2016.Google ScholarGoogle Scholar
  6. E. Androulaki, G. O. Karame, M. Roeschlin, T. Scherer, and S. Capkun. Evaluating user privacy in bitcoin. In International Conference on Financial Cryptography and Data Security, pages 34--51. Springer, 2013.Google ScholarGoogle ScholarCross RefCross Ref
  7. M. Bartoletti and L. Pompianu. An empirical analysis of smart contracts: platforms, applications, and design patterns. In International Conference on Financial Cryptography and Data Security, pages 494--509. Springer, 2017.Google ScholarGoogle ScholarCross RefCross Ref
  8. H. Basil Al Jawaheri, M. Al Sabah, and Y. Boshmaf. Measurement and analysis of bitcoin transactions of ransomware. In Qatar Foundation Annual Research Conference Proceedings, volume 2018, page ICTPD1026. HBKU Press Qatar, 2018.Google ScholarGoogle Scholar
  9. C. Decker and R. Wattenhofer. Information propagation in the bitcoin network. In International Conference on Peer-to-Peer Computing (P2P), pages 1--10. IEEE, 2013.Google ScholarGoogle ScholarCross RefCross Ref
  10. S. Delgado-Segura, C. Pérez-Sola, G. Navarro-Arribas, and J. Herrera-Joancomartı. Analysis of the bitcoin utxo set.Google ScholarGoogle Scholar
  11. A. E. Gencer, S. Basu, I. Eyal, R. van Renesse, and E. G. Sirer. Decentralization in bitcoin and ethereum networks. arXiv preprint arXiv:1801.03998, 2018.Google ScholarGoogle Scholar
  12. A. Hertig. $160 million stuck: Can parity still shake up ethereum? https://www.coindesk.com/startup-lost-160-million-still-wants-shake-ethereum/.Google ScholarGoogle Scholar
  13. L. Kiffer, D. Levin, and A. Mislove. Stick a fork in it: Analyzing the ethereum network partition. In Proceedings of the 16th ACM Workshop on Hot Topics in Networks, pages 94--100. ACM, 2017. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. R. Matzutt, J. Hiller, M. Henze, J. H. Ziegeldorf, D. Müllmann, O. Hohlfeld, and K. Wehrle. A quantitative analysis of the impact of arbitrary blockchain content on bitcoin. In Proceedings of the 22nd International Conference on Financial Cryptography and Data Security (FC). Springer, 2018.Google ScholarGoogle ScholarCross RefCross Ref
  15. P. Maymounkov and D. Mazieres. Kademlia: A peer-to-peer information system based on the xor metric. In International Workshop on Peer-to-Peer Systems, pages 53--65. Springer, 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. S. Meiklejohn, M. Pomarole, G. Jordan, K. Levchenko, D. McCoy, G. M. Voelker, and S. Savage. A fistful of bitcoins: characterizing payments among men with no names. In Internet Measurement Conference, pages 127--140. ACM, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. A. Miller, J. Litton, A. Pachulski, N. Gupta, D. Levin, N. Spring, and B. Bhattacharjee. Discovering bitcoin's public topology and influential nodes. et al., 2015.Google ScholarGoogle Scholar
  18. M. Moser. Anonymity of bitcoin transactions: An analysis of mixing services. In Münster Bitcoin Conference (MBC), 2013.Google ScholarGoogle Scholar
  19. T. Neudecker and H. Hartenstein. Could network information facilitate address clustering in bitcoin? In International Conference on Financial Cryptography and Data Security, pages 155--169. Springer, 2017.Google ScholarGoogle ScholarCross RefCross Ref
  20. R. Norvill, B. B. F. Pontiveros, R. State, I. Awan, and A. Cullen. Automated labeling of unknown contracts in ethereum. In Computer Communication and Networks (ICCCN), 2017 26th International Conference on, pages 1--6. IEEE, 2017.Google ScholarGoogle ScholarCross RefCross Ref
  21. S. Ranshous, C. A. Joslyn, S. Kreyling, K. Nowak, N. F. Samatova, C. L. West, and S. Winters. Exchange pattern mining in the bitcoin transaction directed hypergraph. In International Conference on Financial Cryptography and Data Security, pages 248--263. Springer, 2017.Google ScholarGoogle ScholarCross RefCross Ref
  22. D. Ron and A. Shamir. Quantitative analysis of the full bitcoin transaction graph. In International Conference on Financial Cryptography and Data Security, pages 6--24. Springer, 2013.Google ScholarGoogle ScholarCross RefCross Ref
  23. D. Siegal. Understanding the dao attack. https://www.coindesk.com/understanding-dao-hack-journalists/.Google ScholarGoogle Scholar
  24. M. Vasek and T. Moore. There's no free lunch, even using bitcoin: Tracking the popularity and profits of virtual currency scams. In International conference on financial cryptography and data security, pages 44--61. Springer, 2015.Google ScholarGoogle ScholarCross RefCross Ref
  25. M. Vasek and T. Moore. Analyzing the bitcoin ponzi scheme ecosystem. In Bitcoin Workshop, 2018.Google ScholarGoogle Scholar
  26. G. Wood. Ethereum: A secure decentralised generalised transaction ledger. Ethereum project yellow paper, 151:1--32, 2014.Google ScholarGoogle Scholar

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  • Published in

    cover image ACM Conferences
    IMC '18: Proceedings of the Internet Measurement Conference 2018
    October 2018
    507 pages
    ISBN:9781450356190
    DOI:10.1145/3278532

    Copyright © 2018 ACM

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    Publication History

    • Published: 31 October 2018

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