Document Open Access Logo

A Puff of Steem: Security Analysis of Decentralized Content Curation

Authors Aggelos Kiayias, Benjamin Livshits, Andrés Monteoliva Mosteiro, Orfeas Stefanos Thyfronitis Litos

PDF

File

Thumbnail PDF
PDF
OASIcs.Tokenomics.2019.3.pdf
  • Filesize: 0.69 MB
  • 21 pages

Document Identifiers

Related Versions

Subject Classification

ACM Subject Classification
  • Security and privacy → Distributed systems security
Keywords
  • blockchain
  • content curation
  • decentralized
  • voting

Metrics

  • Access Statistics
  • Total Accesses (updated on a weekly basis)
    0
    PDF Downloads
    0
    Metadata Views

Abstract

Decentralized content curation is the process through which uploaded posts are ranked and filtered based exclusively on users' feedback. Platforms such as the blockchain-based Steemit employ this type of curation while providing monetary incentives to promote the visibility of high quality posts according to the perception of the participants. Despite the wide adoption of the platform very little is known regarding its performance and resilience characteristics. In this work, we provide a formal model for decentralized content curation that identifies salient complexity and game-theoretic measures of performance and resilience to selfish participants. Armed with our model, we provide a first analysis of Steemit identifying the conditions under which the system can be expected to correctly converge to curation while we demonstrate its susceptibility to selfish participant behaviour. We validate our theoretical results with system simulations in various scenarios.

Cite As Get BibTex

Aggelos Kiayias, Benjamin Livshits, Andrés Monteoliva Mosteiro, and Orfeas Stefanos Thyfronitis Litos. A Puff of Steem: Security Analysis of Decentralized Content Curation. In International Conference on Blockchain Economics, Security and Protocols (Tokenomics 2019). Open Access Series in Informatics (OASIcs), Volume 71, pp. 3:1-3:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020) https://doi.org/10.4230/OASIcs.Tokenomics.2019.3

Author Details

Aggelos Kiayias
  • University of Edinburgh, United Kingdom
  • IOHK, Hong Kong
Benjamin Livshits
  • Imperial College of London, United Kingdom
  • Brave Software, United Kingdom
Andrés Monteoliva Mosteiro
  • University of Edinburgh, United Kingdom
  • Clearmatics, London, United Kingdom
Orfeas Stefanos Thyfronitis Litos
  • University of Edinburgh, United Kingdom

References

  1. Zeinab Abbassi, Nidhi Hegde, and Laurent Massoulié. Distributed content curation on the Web. ACM Transactions on Internet Technology (TOIT), 14(2-3):9, 2014. Google Scholar
  2. Ashton Anderson, Daniel Huttenlocher, Jon Kleinberg, and Jure Leskovec. Steering user behavior with badges. In Proceedings of the 22nd international conference on World Wide Web, pages 95-106. ACM, 2013. Google Scholar
  3. Georgios Askalidis and Greg Stoddard. A theoretical analysis of crowdsourced content curation. In The 3rd Workshop on Social Computing and User Generated Content, volume 16, 2013. Google Scholar
  4. Kelly Bergstrom. "Don't feed the troll": Shutting down debate about community expectations on Reddit. com. First Monday, 16(8), 2011. Google Scholar
  5. Vitalik Buterin. Notes on Blockchain Governance. Accessed: 2019-01-02, 2017. URL: https://vitalik.ca/general/2017/12/17/voting.html.
  6. Vincent Conitzer and Tuomas Sandholm. Communication complexity of common voting rules. In Proceedings of the 6th ACM conference on Electronic commerce, pages 78-87. ACM, 2005. Google Scholar
  7. Philip Daian, Tyler Kell, Ian Miers, and Ari Juels. On-Chain Vote Buying and the Rise of Dark DAOs. Accessed: 2019-01-02, 2018. URL: http://hackingdistributed.com/2018/07/02/on-chain-vote-buying/.
  8. dantheman. DPOS Consensus Algorithm - The Missing White Paper. URL: https://steemit.com/dpos/@dantheman/dpos-consensus-algorithm-this-missing-white-paper Accessed: 2019-04-02, 2017.
  9. Anish Das Sarma, Atish Das Sarma, Sreenivas Gollapudi, and Rina Panigrahy. Ranking mechanisms in twitter-like forums. In Proceedings of the third ACM international conference on Web search and data mining, pages 21-30. ACM, 2010. Google Scholar
  10. J. R. Douceur. The Sybil Attack. International workshop on Peer-To-Peer Systems, 2002. Google Scholar
  11. Evan Duffield and Daniel Diaz. Dash: A PrivacyCentric CryptoCurrency. Self-published, 2015. Google Scholar
  12. Fred Ehrsam. Blockchain Governance: Programming Our Future. https://www.medium.com, 2017. Accessed: 2019-01-02. URL: https://www.medium.com/@FEhrsam/blockchain-governance-programming-our-future-c3bfe30f2d74.
  13. Andrea Forte and Amy Bruckman. Scaling consensus: Increasing decentralization in Wikipedia governance. In Hawaii International Conference on System Sciences, Proceedings of the 41st Annual, pages 157-157. IEEE, 2008. Google Scholar
  14. Arpita Ghosh and Preston McAfee. Incentivizing high-quality user-generated content. In Proceedings of the 20th international conference on World wide web, pages 137-146. ACM, 2011. Google Scholar
  15. Allan Gibbard. Manipulation of voting schemes: a general result. Econometrica: journal of the Econometric Society, pages 587-601, 1973. Google Scholar
  16. Mike Goldin. Token-Curated Registries 1.0. Accessed: 2019-01-02, 2017. URL: https://medium.com/@ilovebagels/token-curated-registries-1-0-61a232f8dac7.
  17. Oded Goldreich. The foundations of modern cryptography. In Modern Cryptography, Probabilistic Proofs and Pseudorandomness, pages 1-37. Springer, 1999. Google Scholar
  18. Julián González. Author and Curator rewards in HF19. Accessed: 2019-01-02, 2018. URL: https://steemit.com/steemit/@jga/author-and-curator-rewards-in-hf19.
  19. Julián González. Self-voters can achieve an interest of 248%APR!! URL: https://steemit.com/utopian-io/@jga/self-voters-can-achieve-an-interest-of-248-apr. Accessed: 2019-01-02, 2018.
  20. LM Goodman. Tezos-a self-amending crypto-ledger White paper. URL: https://www.tezos.com/static/papers/white_paper.pdf, 2014.
  21. Mangesh Gupte, MohammadTaghi Hajiaghayi, Lu Han, Liviu Iftode, Pravin Shankar, and Raluca M Ursu. News posting by strategic users in a social network. In International Workshop on Internet and Network Economics, pages 632-639. Springer, 2009. Google Scholar
  22. Claude Hillinger. The case for utilitarian voting. Homo Oeconomicus, 22(3), 2005. . Accessed: 2019-04-01. URL: https://ssrn.com/abstract=878008.
  23. Meir Kalech, Sarit Kraus, Gal A Kaminka, and Claudia V Goldman. Practical voting rules with partial information. Autonomous Agents and Multi-Agent Systems, 22(1):151-182, 2011. Google Scholar
  24. Andreas M Kaplan and Michael Haenlein. Users of the world, unite! The challenges and opportunities of Social Media. Business horizons, 53(1):59-68, 2010. Google Scholar
  25. Maurice G Kendall. Rank Correlation Methods, volume 9, page 68. Hafner Publishing Co., 2 edition, 1955. . Accessed: 2019-04-01. URL: https://doi.org/10.1111/j.2044-8317.1956.tb00172.x.
  26. Aggelos Kiayias, Benjamin Livshits, Andrés Monteoliva Mosteiro, and Orfeas Stefanos Thyfronitis Litos. A Puff of Steem: Security Analysis of Decentralized Content Curation. arxiv.org, 2018. Google Scholar
  27. Dor Konforty, Yuval Adam, Daniel Estrada, and Lucius Gregory Meredith. Synereo: The Decentralized and Distributed Social Network. Self-published, 2015. Accessed: 2019-01-02. URL: https://pdfs.semanticscholar.org/253c/c4744e6b2b87f88e46188fe527982b19542e.pdf.
  28. Jure Leskovec, Daniel P Huttenlocher, and Jon M Kleinberg. Governance in social media: A case study of the wikipedia promotion process. In ICWSM, pages 98-105, 2010. Google Scholar
  29. Brian Neil Levine, Clay Shields, and N Boris Margolin. A survey of solutions to the sybil attack. University of Massachusetts Amherst, Amherst, MA, 7:224, 2006. Google Scholar
  30. Yehuda Lindell and Jonathan Katz. Introduction to modern cryptography. Chapman and Hall/CRC, 2014. Google Scholar
  31. Tyler Lu and Craig Boutilier. Robust approximation and incremental elicitation in voting protocols. In IJCAI, volume 1, pages 287-293, 2011. Google Scholar
  32. Avner May, Augustin Chaintreau, Nitish Korula, and Silvio Lattanzi. Filter &follow: How social media foster content curation. In ACM SIGMETRICS Performance Evaluation Review, volume 42, pages 42-55. ACM, 2014. Google Scholar
  33. Pasquale De Meo, Katarzyna Musial-Gabrys, Domenico Rosaci, Giuseppe ML Sarne, and Lora Aroyo. Using centrality measures to predict helpfulness-based reputation in trust networks. ACM Transactions on Internet Technology (TOIT), 17(1):8, 2017. Google Scholar
  34. Arash Molavi Kakhki, Chloe Kliman-Silver, and Alan Mislove. Iolaus: Securing online content rating systems. In Proceedings of the 22nd international conference on World Wide Web, pages 919-930. ACM, 2013. Google Scholar
  35. Emilee Rader and Rebecca Gray. Understanding user beliefs about algorithmic curation in the Facebook news feed. In Proceedings of the 33rd annual ACM conference on human factors in computing systems, pages 173-182. ACM, 2015. Google Scholar
  36. Fabian Schuh. Graphene Documentation. Accessed: 2019-04-02, 2018. URL: https://media.readthedocs.org/pdf/docsbitsharesorg/master/docsbitsharesorg.pdf.
  37. Charles Spearman. The proof and measurement of association between two things. The American journal of psychology, 15(1):72-101, 1904. Google Scholar
  38. Katarina Stanoevska-Slabeva, Vittoria Sacco, and Marco Giardina. Content Curation: a new form of gatewatching for social media. In Proceedings of the 12th international symposium on online journalism, 2012. Google Scholar
  39. Mike Thelwall. Can social news websites pay for content and curation? The SteemIt cryptocurrency model. Journal of Information Science, page 0165551517748290, 2017. Google Scholar
  40. Dinh Nguyen Tran, Bonan Min, Jinyang Li, and Lakshminarayanan Subramanian. Sybil-Resilient Online Content Voting. In NSDI, volume 9, pages 15-28, 2009. Google Scholar
  41. Unknown. Steem: An incentivized, blockchain-based, public content platform. Accessed: 2019-04-02, 2017. URL: https://steem.com/SteemWhitePaper.pdf.
  42. Unknown. Steem Whitepaper. Accessed: 2019-04-02, 2018. URL: https://steem.io/steem-whitepaper.pdf.
  43. Bimal Viswanath, Mainack Mondal, Krishna P Gummadi, Alan Mislove, and Ansley Post. Canal: Scaling social network-based Sybil tolerance schemes. In Proceedings of the 7th ACM european conference on Computer Systems, pages 309-322. ACM, 2012. Google Scholar
  44. Lirong Xia and Vincent Conitzer. Compilation Complexity of Common Voting Rules. In AAAI, 2010. Google Scholar
  45. Haifeng Yu, Chenwei Shi, Michael Kaminsky, Phillip B Gibbons, and Feng Xiao. Dsybil: Optimal sybil-resistance for recommendation systems. In 2009 30th IEEE Symposium on Security and Privacy, pages 283-298. IEEE, 2009. Google Scholar
  46. Yingwu Zhu. Measurement and analysis of an online content voting network: a case study of Digg. In Proceedings of the 19th international conference on World wide web, pages 1039-1048. ACM, 2010. Google Scholar
Questions / Remarks / Feedback
X

Feedback for Dagstuhl Publishing


Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail
© 2023-2025 Schloss Dagstuhl – LZI GmbH About DROPS Imprint Privacy Contact