Prediction of Bitcoin Price using Data Mining

Dandelion++: Lightweight Cryptocurrency Networking with Formal Anonymity Guarantees

Date: 2018-05-28
Author(s): Giulia Fanti, Shaileshh Bojja Venkatakrishnan, Surya Bakshi, Bradley Denby, Shruti Bhargava, Andrew Miller, Pramod Viswanath

Link to Paper

Recent work has demonstrated significant anonymity vulnerabilities in Bitcoin's networking stack. In particular, the current mechanism for broadcasting Bitcoin transactions allows third-party observers to link transactions to the IP addresses that originated them. This lays the groundwork for low-cost, large-scale deanonymization attacks. In this work, we present Dandelion++, a first-principles defense against large-scale deanonymization attacks with near-optimal information-theoretic guarantees. Dandelion++ builds upon a recent proposal called Dandelion that exhibited similar goals. However, in this paper, we highlight simplifying assumptions made in Dandelion, and show how they can lead to serious deanonymization attacks when violated. In contrast, Dandelion++ defends against stronger adversaries that are allowed to disobey protocol. Dandelion++ is lightweight, scalable, and completely interoperable with the existing Bitcoin network. We evaluate it through experiments on Bitcoin's mainnet (i.e., the live Bitcoin network) to demonstrate its interoperability and low broadcast latency overhead.

[1] [n. d.]. AWS Regions and Endpoints. ([n. d.]).
[2] [n. d.]. Bitcoin Core integration/staging tree. ([n. d.]).
[3] [n. d.]. Chainalysis. ([n. d.]).
[4] [n. d.]. The Kovri I2P Router Project. ([n. d.]).
[5] [n. d.]. Monero. ([n. d.]).
[6] 2015. Bitcoin Core Commit 5400ef6. (2015).
[7] 2016. reddit/monero. (2016).
[8] Elli Androulaki, Ghassan O Karame, Marc Roeschlin, Tobias Scherer, and Srdjan Capkun. 2013. Evaluating user privacy in bitcoin. In International Conference on Financial Cryptography and Data Security. Springer, 34–51.
[9] Maria Apostolaki, Aviv Zohar, and Laurent Vanbever. 2016. Hijacking Bitcoin: Large-scale Network Attacks on Cryptocurrencies. arXiv preprint arXiv:1605.07524 (2016).
[10] Krishna B Athreya and Peter E Ney. 2004. Branching processes. Courier Corporation.
[11] Alex Biryukov, Dmitry Khovratovich, and Ivan Pustogarov. 2014. Deanonymisation of clients in Bitcoin P2P network. In Proceedings of the 2014 ACM SIGSAC Conference on Computer and Communications Security. ACM, 15–29.
[12] Alex Biryukov and Ivan Pustogarov. 2015. Bitcoin over Tor isn’t a good idea. In Symposium on Security and Privacy. IEEE, 122–134.
[13] John Bohannon. 2016. Why criminals can’t hide behind Bitcoin. Science (2016).
[14] Shaileshh Bojja Venkatakrishnan, Giulia Fanti, and Pramod Viswanath. 2017. Dandelion: Redesigning the Bitcoin Network for Anonymity. POMACS 1, 1 (2017), 22.
[15] D. Chaum. 1988. The dining cryptographers problem: Unconditional sender and recipient untraceability. Journal of cryptology 1, 1 (1988).
[16] Ramnath K Chellappa and Raymond G Sin. 2005. Personalization versus privacy: An empirical examination of the online consumer’s dilemma. Information technology and management 6, 2 (2005), 181–202.
[17] H. Corrigan-Gibbs and B. Ford. 2010. Dissent: accountable anonymous group messaging. In CCS. ACM.
[18] George Danezis, Claudia Diaz, Emilia Käsper, and Carmela Troncoso. 2009. The wisdom of Crowds: attacks and optimal constructions. In European Symposium on Research in Computer Security. Springer, 406–423.
[19] George Danezis, Claudia Diaz, Carmela Troncoso, and Ben Laurie. 2010. Drac: An Architecture for Anonymous Low-Volume Communications.. In Privacy Enhancing Technologies, Vol. 6205. Springer, 202–219.
[20] R. Dingledine, N. Mathewson, and P. Syverson. 2004. Tor: The second-generation onion router. Technical Report. DTIC Document.
[21] G. Fanti, P. Kairouz, S. Oh, and P. Viswanath. 2015. Spy vs. Spy: Rumor Source Obfuscation. In SIGMETRICS Perform. Eval. Rev., Vol. 43. 271–284. Issue 1.
[22] Giulia Fanti and Pramod Viswanath. 2017. Anonymity Properties of the Bitcoin P2P Network. arXiv preprint arXiv:1703.08761 (2017).
[23] M.J. Freedman and R. Morris. 2002. Tarzan: A peer-to-peer anonymizing network layer. In Proc. CCS. ACM.
[24] Sam Frizell. 2015. Bitcoins Are Easier To Track Than You Think. Time (January 2015).
[25] Adam Efe Gencer and Emin Gün Sirer. 2017. State of the Bitcoin Network. Hacking Distributed, (February 2017).
[26] S. Goel, M. Robson, M. Polte, and E. Sirer. 2003. Herbivore: A scalable and efficient protocol for anonymous communication. Technical Report.
[27] P. Golle and A. Juels. 2004. Dining cryptographers revisited. In Advances in Cryptology-Eurocrypt 2004.
[28] Ethan Heilman, Leen Alshenibr, Foteini Baldimtsi, Alessandra Scafuro, and Sharon Goldberg. 2016. TumbleBit: An untrusted Bitcoin-compatible anonymous payment hub. Technical Report. Cryptology ePrint Archive, Report 2016/575.
[29] TE Jedusor. 2016. Mimblewimble. (2016).
[30] Philip Koshy. 2013. CoinSeer: A Telescope Into Bitcoin. Ph.D. Dissertation. The Pennsylvania State University.
[31] Philip Koshy, Diana Koshy, and Patrick McDaniel. 2014. An analysis of anonymity in bitcoin using p2p network traffic. In International Conference on Financial Cryptography and Data Security. Springer, 469–485.
[32] Greg Maxwell. 2013. CoinJoin: Bitcoin privacy for the real world. In Post on Bitcoin Forum.
[33] Dave McMillen. 2017. Mirai IoT Botnet: Mining for Bitcoins? SecurityIntelligence (April 2017).
[34] Sarah Meiklejohn, Marjori Pomarole, Grant Jordan, Kirill Levchenko, Damon McCoy, Geoffrey M Voelker, and Stefan Savage. 2013. A fistful of bitcoins: characterizing payments among men with no names. In Proceedings of the 2013 conference on Internet measurement conference. ACM, 127–140.
[35] Marc Mezard and Andrea Montanari. 2009. Information, physics, and computation. Oxford University Press.
[36] Andrew Miller, James Litton, Andrew Pachulski, Neal Gupta, Dave Levin, Neil Spring, and Bobby Bhattacharjee. 2015. Discovering Bitcoin’s public topology and influential nodes. (2015).
[37] Prateek Mittal, Matthew Wright, and Nikita Borisov. 2013. Pisces: Anonymous communication using social networks. In NDSS. ACM.
[38] Satoshi Nakamoto. 2008. Bitcoin: A peer-to-peer electronic cash system. (2008).
[39] Micha Ober, Stefan Katzenbeisser, and Kay Hamacher. 2013. Structure and anonymity of the bitcoin transaction graph. Future internet 5, 2 (2013), 237–250.
[40] Larry L Peterson and Bruce S Davie. 2007. Computer networks: a systems approach. Elsevier.
[41] P. C. Pinto, P. Thiran, and M. Vetterli. 2012. Locating the source of diffusion in large-scale networks. Physical review letters 109, 6 (2012), 068702.
[42] Fergal Reid and Martin Harrigan. 2013. An analysis of anonymity in the bitcoin system. In Security and privacy in social networks. Springer, 197–223.
[43] Michael K Reiter and Aviel D Rubin. 1998. Crowds: Anonymity for web transactions. ACM Transactions on Information and System Security (TISSEC) 1, 1 (1998), 66–92.
[44] Dorit Ron and Adi Shamir. 2013. Quantitative analysis of the full bitcoin transaction graph. In International Conference on Financial Cryptography and Data Security. Springer, 6–24.
[45] Tim Ruffing, Pedro Moreno-Sanchez, and Aniket Kate. 2014. CoinShuffle: Practical decentralized coin mixing for Bitcoin. In European Symposium on Research in Computer Security. Springer, 345–364.
[46] Eli Ben Sasson, Alessandro Chiesa, Christina Garman, Matthew Green, Ian Miers, Eran Tromer, and Madars Virza. 2014. Zerocash: Decentralized anonymous payments from bitcoin. In Symposium on Security and Privacy. IEEE, 459–474.
[47] Alexander Schrijver. 2002. Combinatorial optimization: polyhedra and efficiency. Vol. 24. Springer Science & Business Media.
[48] Rob Sherwood, Bobby Bhattacharjee, and Aravind Srinivasan. 2005. P5: A protocol for scalable anonymous communication. Journal of Computer Security 13, 6 (2005), 839–876.
[49] Jelle van den Hooff, David Lazar, Matei Zaharia, and Nickolai Zeldovich. [n. d.]. Scalable Private Messaging Resistant to Traffic Analysis. ([n. d.]).
[50] Zhaoxu Wang, Wenxiang Dong, Wenyi Zhang, and Chee Wei Tan. 2014. Rumor source detection with multiple observations: Fundamental limits and algorithms. In ACM SIGMETRICS Performance Evaluation Review, Vol. 42. ACM, 1–13.
[51] David Isaac Wolinsky, Henry Corrigan-Gibbs, Bryan Ford, and Aaron Johnson. 2012. Dissent in Numbers: Making Strong Anonymity Scale.. In OSDI. 179–182.
[52] M. Zamani, J. Saia, M. Movahedi, and J. Khoury. 2013. Towards provably-secure scalable anonymous broadcast. In USENIX FOCI.
[53] Bassam Zantout and Ramzi Haraty. 2011. I2P data communication system. In Proceedings of ICN. Citeseer, 401–409.
[54] Kai Zhu and Lei Ying. 2014. A robust information source estimator with sparse observations. Computational Social Networks 1, 1 (2014), 3.
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An Analysis of Attacks on Blockchain Consensus

Date: 2016-11-20
Author(s): George Bissias, Brian Neil Levine, A. Pinar Ozisik, Gavin Andresen

Link to Paper

We present and validate a novel mathematical model of the blockchain mining process and use it to conduct an economic evaluation of the double-spend attack, which is fundamental to all blockchain systems. Our analysis focuses on the value of transactions that can be secured under a conventional double-spend attack, both with and without a concurrent eclipse attack. Our model quantifies the importance of several factors that determine the attack's success, including confirmation depth, attacker mining power, and any confirmation deadline set by the merchant. In general, the security of a transaction against a double-spend attack increases roughly logarithmically with the depth of the block, made easier by the increasing sum of coin turned-over (between individuals) in the blocks, but more difficult by the increasing proof of work required. In recent blockchain data, we observed a median block turnover value of 6 BTC. Based on this value, a merchant requiring a single confirmation is protected against only attackers that can increase the current mining power by 1% or less. However, similar analysis shows that a merchant that requires a much longer 72 confirmations (~12 hours) will eliminate all potential profit for any double-spend attacker adding mining power less than 40% of the current mining power.

  1. Back, A., Corallo, M., Dashjr, L., Mark, F., Maxwell, G., Miller, A., Poelstra, A., Timón, J., Wuille, P.: Enabling Blockchain Innovations with Pegged Sidechains. (October 2014)
  2. Bissias, G., Ozisik, A.P., Levine, B.N., Liberatore, M.: Sybil-Resistant Mixing for Bitcoin. In: Proc. ACM Workshop on Privacy in the Electronic Society (November 2014),
  3. Confirmation. (February 2015)
  4. Bonneau, J., Miller, A., Clark, J., Narayanan, A., Kroll, J., Felten, E.: Sok: Research perspectives and challenges for bitcoin and cryptocurrencies. In: IEEE S&P. pp. 104–121 (May 2015),
  5. Bonneau, J.: How long does it take for a bitcoin transaction to be confirmed? (November 2015)
  6. Croman, K., et al.: On Scaling Decentralized Blockchains . In: Workshop on Bitcoin and Blockchain Research (Feb 2016)
  7. Douceur, J.: The Sybil Attack. In: Proc. Intl Wkshp on Peer-to-Peer Systems (IPTPS) (Mar 2002)
  8. Ethereum Homestead Documentation.
  9. Eyal, I., Sirer, E.G.: Majority Is Not Enough: Bitcoin Mining Is Vulnerable. Financial Cryptography pp. 436–454 (2014),
  10. Fischer, M., Lynch, N., Paterson, M.: Impossibility of distributed consensus with one faulty process. JACM 32(2), 374–382 (1985)
  11. Gervais, A., O. Karame, G., Wust, K., Glykantzis, V., Ritzdorf, H., Capkun, S.: On the Security and Performance of Proof of Work Blockchains. (2016)
  12. Heilman, E., Alshenibr, L., Baldimtsi, F., Scafuro, A., Goldberg, S.: Tumblebit: An untrusted bitcoin-compatible anonymous payment hub. Cryptology ePrint Archive, Report 2016/575 (2016),
  13. Heilman, E., Kendler, A., Zohar, A., Goldberg, S.: Eclipse Attacks on Bitcoin’s Peer-to-peer Network. In: USENIX Security (2015)
  14. Litecoin.
  15. Meiklejohn, S., Pomarole, M., Jordan, G., Levchenko, K., McCoy, D., Voelker, G., Savage, S.: A Fistful of Bitcoins: Characterizing Payments Among Men with No Names. In: Proc. ACM IMC. pp. 127–140 (2013),
  16. Nakamoto, S.: Bitcoin: A Peer-to-Peer Electronic Cash System. (May 2009)
  17. Pagnia, H., Vogt, H., Gaertner, F.: Fair Exchange. The Computer Journal, vol. 46, num. 1, p. 55, 2003. 46(1), 55–78 (2003)
  18. Poon, J., Dryja, T.: The Bitcoin Lightning Network: Scalable Off-Chain Instant Payments. (November 2015)
  19. Ron, D., Shamir, A.: Quantitative analysis of the full bitcoin transaction graph. In: Proc. Financial Crypto. pp. 6–24 (Apr 2013),
  20. Rosenfeld, M.: Analysis of hashrate-based double-spending. (December 2012)
  21. Sapirshtein, A., Sompolinsky, Y., Zohar, A.: Optimal Selfish Mining Strategies in Bitcoin. (July 2015)
  22. Sasson, E.B., Chiesa, A., Garman, C., Green, M., Miers, I., Tromer, E., Virza, M.: Zerocash: Decentralized anonymous payments from bitcoin. In: IEEE S&P. pp. 459–474 (2014),
  23. Sompolinsky, Y., Zohar, A.: Secure high-rate transaction processing in Bitcoin. Financial Cryptography and Data Security (2015),
  24. Sompolinsky, Y., Zohar, A.: Bitcoin’s Security Model Revisited. (May 2016)
  25. Tschorsch, F., Scheuermann, B.: Bitcoin and beyond: A technical survey on decentralized digital currencies. IEEE Communications Surveys Tutorials PP(99), 1–1 (2016)
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IOHK  Consensus protocols - proof of stake and proof of work BlockChain class3 Jan3 Nodes and ConsensusWhat is AES RSA Cryptography తెలుగులో I 9985269518

Bitcoin Mining Pools: A Cooperative Game Theoretic Analysis. Pages 919–927. Previous Chapter Next Chapter. ABSTRACT . Bitcoin is an innovative decentralized cryptocurrency whose core security relies on a "proof of work" procedure, which requires network participants to repeatedly compute hashes on inputs from a large search space. Finding one of the rare inputs that generates an extremely ... Bitcoin is a decentralized cryptocurrency payment system, working without a single administrator or a third party bank. A bitcoin is created by miners, using complex mathematical “proof of work” procedure by computing hashes. For each successful attempt, miners get rewards in terms of bitcoin and transaction fees. Miners participate in mining to get this reward as income. [ Die Forscher Dorit Ron und Adi Shamir analysierten im Mai 2012 den Transaktionsgraphen und ermittelten eine Zahl von 2,4 Millionen unabhängig verwendeten Adressen. Diese Zahl stellt eine Obergrenze der Nutzer dar, die bis zu dem Zeitpunkt eine Bitcoin-Transaktion durchgeführt haben. Die aktivsten Einzelnutzer waren der Mining Pool Deepbit und die Handelsplattform Mt.Gox, verantwortlich ... How to begin Bitcoin mining for newbies. In October 2013, the FBI seized roughly 26,000 BTC from web site Silk Road through the arrest of alleged proprietor Ross William Ulbricht. Two companies, Robocoin and Bitcoiniacs launched the world’s first bitcoin ATM on 29 October 2013 in Vancouver, BC, Canada, permitting clients to promote or buy bitcoin currency at a downtown espresso shop. Chinese ... Exchange Pattern Mining in the Bitcoin Transaction Directed Hypergraph. Authors; Authors and affiliations; Stephen Ranshous; Cliff A. Joslyn; Sean Kreyling; Kathleen Nowak; Nagiza F. Samatova ; Curtis L. West; Samuel Winters; Conference paper. First Online: 19 November 2017. 11 Citations; 3k Downloads; Part of the Lecture Notes in Computer Science book series (LNCS, volume 10323) Abstract ...

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IOHK Consensus protocols - proof of stake and proof of work

Leading cryptographers at the conference included Whitfield Diffie, pioneer of the public key cryptography that made Bitcoin possible, and Ron Rivest, Adi Shamir, and Leonard Adleman, who came up ... Ron Rivest, Adi Shamir, and Leonard Adleman invented the RSA cipher in 1978 in response to the ideas proposed by Hellman, Diffie, and Merkel. Later in this chapter, we shall see how to use the ...