Abstract Bitcoin relies on a peer-to-peer overlay network to broadcast transactions and blocks. From the viewpoint of network measurement, we would like to observe this topology so we can characterize its performance, fairness and robustness. However, this is difficult because Bitcoin is deliberately designed to hide its topology from onlookers. Knowledge of the topology is not in itself a vulnerability, although it could conceivably help an attacker performing targeted eclipse attacks or to deanonymize transaction senders. In this paper we present TxProbe, a novel technique for reconstructing the Bitcoin network topology. TxProbe makes use of peculiarities in how Bitcoin processes out of order, or "orphaned" transactions. We conducted experiments on Bitcoin testnet that suggest our technique reconstructs topology with precision and recall surpassing 90%. We also used TxProbe to take a snapshot of the Bitcoin testnet in just a few hours. TxProbe may be useful for future measurement campaigns of Bitcoin or other cryptocurrency networks. References
Albert, R., Barabási, A.: Statistical mechanics of complex networks. CoRR condmat/0106096 (2001)
Biryukov, A., Khovratovich, D., Pustogarov, I.: Deanonymisation of clients in bitcoin p2p network. In: Proceedings of the 2014 ACM SIGSAC Conference on Computer and Communications Security. pp. 15–29. CCS ’14, ACM, New York, NY, USA (2014)
Biryukov, A., Pustogarov, I.: Bitcoin over tor isn’t a good idea. In: Proceedings of the 2015 IEEE Symposium on Security and Privacy. pp. 122–134. SP ’15, IEEE Computer Society, Washington, DC, USA (2015), https://doi.org/10.1109/SP.2015.15
Erdös, P., Rényi, A.: On the evolution of random graphs. In: Math. Inst. Hungar. Acad. Sci. pp. 17–61 (1960)
Gencer, A.E., Basu, S., Eyal, I., van Renesse, R., Sirer, E.G.: Decentralization in bitcoin and ethereum networks (2018)
Grundmann, M., Neudecker, T., Hartenstein, H.: Exploiting transaction accumulation and double spends for topology inference in bitcoin. In: Financial Cryptography and Data Security. Springer International Publishing (2018)
Heilman, E., Kendler, A., Zohar, A., Goldberg, S.: Eclipse attacks on bitcoin’s peer-to-peer network. In: 24th USENIX Security Symposium (USENIX Security 15). pp. 129–144. USENIX Association, Washington, D.C. (2015)
Jansen, R., Johnson, A.: Safely measuring tor. In: Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security. pp. 1553–1567. ACM (2016)
Koshy, P., Koshy, D., McDaniel, P.: An analysis of anonymity in bitcoin using p2p network traffic. In: Christin, N., Safavi-Naini, R. (eds.) Financial Cryptography and Data Security. pp. 469–485. Springer Berlin Heidelberg, Berlin, Heidelberg (2014)
Miller, A., Litton, J., Pachulski, A., Gupta, N., Levin, D., Spring, N., Bhattacharjee, B.: Discovering bitcoin’s public topology and influential nodes (2015)
Nayak, K., Kumar, S., Miller, A., Shi, E.: Stubborn mining: Generalizing selfish mining and combining with an eclipse attack. In: 2016 IEEE European Symposium on Security and Privacy (EuroS P). pp. 305–320 (March 2016)
Neudecker, T., Andelfinger, P., Hartenstein, H.: Timing analysis for inferring the topology of the bitcoin peer-to-peer network. In: 2016 Intl IEEE Conferences on Ubiquitous Intelligence Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People, and Smart World Congress (UIC/ATC/ScalCom/CBDCom/IoP/SmartWorld). pp. 358–367 (July 2016)
Neudecker, T., Hartenstein, H.: Could network information facilitate address clustering in bitcoin? In: Brenner, M., Rohloff, K., Bonneau, J., Miller, A., Ryan, P.Y., Teague, V., Bracciali, A., Sala, M., Pintore, F., Jakobsson, M. (eds.) Financial Cryptography and Data Security. pp. 155–169. Springer International Publishing, Cham (2017)
Newman, M.E.: The structure and function of complex networks. SIAM review 45(2), 167–256 (2003)
Abstract 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. References  [n. d.]. AWS Regions and Endpoints. ([n. d.]). http://docs.aws.amazon.com/general/latest/grande.html.  [n. d.]. Bitcoin Core integration/staging tree. ([n. d.]). https://github.com/bitcoin/bitcoin.  [n. d.]. Chainalysis. ([n. d.]). https://www.chainalysis.com/.  [n. d.]. The Kovri I2P Router Project. ([n. d.]). https://github.com/monero-project/kovri.  [n. d.]. Monero. ([n. d.]). https://getmonero.org/home.  2015. Bitcoin Core Commit 5400ef6. (2015). https://github.com/bitcoin/bitcoin/commit/5400ef6bcb9d243b2b21697775aa6491115420f3.  2016. reddit/monero. (2016). https://www.reddit.com/Monero/comments/4aki0k/what_is_the_status_of_monero_and_i2p/.  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.  Maria Apostolaki, Aviv Zohar, and Laurent Vanbever. 2016. Hijacking Bitcoin: Large-scale Network Attacks on Cryptocurrencies. arXiv preprint arXiv:1605.07524 (2016).  Krishna B Athreya and Peter E Ney. 2004. Branching processes. Courier Corporation.  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.  Alex Biryukov and Ivan Pustogarov. 2015. Bitcoin over Tor isn’t a good idea. In Symposium on Security and Privacy. IEEE, 122–134.  John Bohannon. 2016. Why criminals can’t hide behind Bitcoin. Science (2016).  Shaileshh Bojja Venkatakrishnan, Giulia Fanti, and Pramod Viswanath. 2017. Dandelion: Redesigning the Bitcoin Network for Anonymity. POMACS 1, 1 (2017), 22.  D. Chaum. 1988. The dining cryptographers problem: Unconditional sender and recipient untraceability. Journal of cryptology 1, 1 (1988).  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.  H. Corrigan-Gibbs and B. Ford. 2010. Dissent: accountable anonymous group messaging. In CCS. ACM.  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.  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.  R. Dingledine, N. Mathewson, and P. Syverson. 2004. Tor: The second-generation onion router. Technical Report. DTIC Document.  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.  Giulia Fanti and Pramod Viswanath. 2017. Anonymity Properties of the Bitcoin P2P Network. arXiv preprint arXiv:1703.08761 (2017).  M.J. Freedman and R. Morris. 2002. Tarzan: A peer-to-peer anonymizing network layer. In Proc. CCS. ACM.  Sam Frizell. 2015. Bitcoins Are Easier To Track Than You Think. Time (January 2015).  Adam Efe Gencer and Emin Gün Sirer. 2017. State of the Bitcoin Network. Hacking Distributed, http://hackingdistributed.com/2017/02/15/state-of-the-bitcoin-network/. (February 2017).  S. Goel, M. Robson, M. Polte, and E. Sirer. 2003. Herbivore: A scalable and efficient protocol for anonymous communication. Technical Report.  P. Golle and A. Juels. 2004. Dining cryptographers revisited. In Advances in Cryptology-Eurocrypt 2004.  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.  TE Jedusor. 2016. Mimblewimble. (2016).  Philip Koshy. 2013. CoinSeer: A Telescope Into Bitcoin. Ph.D. Dissertation. The Pennsylvania State University.  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.  Greg Maxwell. 2013. CoinJoin: Bitcoin privacy for the real world. In Post on Bitcoin Forum.  Dave McMillen. 2017. Mirai IoT Botnet: Mining for Bitcoins? SecurityIntelligence (April 2017).  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.  Marc Mezard and Andrea Montanari. 2009. Information, physics, and computation. Oxford University Press.  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).  Prateek Mittal, Matthew Wright, and Nikita Borisov. 2013. Pisces: Anonymous communication using social networks. In NDSS. ACM.  Satoshi Nakamoto. 2008. Bitcoin: A peer-to-peer electronic cash system. (2008).  Micha Ober, Stefan Katzenbeisser, and Kay Hamacher. 2013. Structure and anonymity of the bitcoin transaction graph. Future internet 5, 2 (2013), 237–250.  Larry L Peterson and Bruce S Davie. 2007. Computer networks: a systems approach. Elsevier.  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.  Fergal Reid and Martin Harrigan. 2013. An analysis of anonymity in the bitcoin system. In Security and privacy in social networks. Springer, 197–223.  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.  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.  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.  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.  Alexander Schrijver. 2002. Combinatorial optimization: polyhedra and efficiency. Vol. 24. Springer Science & Business Media.  Rob Sherwood, Bobby Bhattacharjee, and Aravind Srinivasan. 2005. P5: A protocol for scalable anonymous communication. Journal of Computer Security 13, 6 (2005), 839–876.  Jelle van den Hooff, David Lazar, Matei Zaharia, and Nickolai Zeldovich. [n. d.]. Scalable Private Messaging Resistant to Traffic Analysis. ([n. d.]).  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.  David Isaac Wolinsky, Henry Corrigan-Gibbs, Bryan Ford, and Aaron Johnson. 2012. Dissent in Numbers: Making Strong Anonymity Scale.. In OSDI. 179–182.  M. Zamani, J. Saia, M. Movahedi, and J. Khoury. 2013. Towards provably-secure scalable anonymous broadcast. In USENIX FOCI.  Bassam Zantout and Ramzi Haraty. 2011. I2P data communication system. In Proceedings of ICN. Citeseer, 401–409.  Kai Zhu and Lei Ying. 2014. A robust information source estimator with sparse observations. Computational Social Networks 1, 1 (2014), 3.
How crazy is this? (A protocol for metadata obfuscation)
Alice and Bob want to have a private conversation but they also don't want anyone to know they're talking to each other. I'm assuming that they can use some public key cryptography protocol that's sufficient to ensure their conversation is indeed private. Alice encrypts her messages using Bob's public key, and her encrypted messages can only be decrypted with Bob's private key. But what about the metadata, ie the who/what/when/where information that we now know is collected routinely by the NSA, and which allows an adversary to determine that Alice and Bob are in communication? As I understand it, there are several more or less practical ways to obscure the metadata -- including the identity of the intended recipient -- of Alice's and Bob's messages. These methods include steganography, TOpluggable transports, anonymizing email services and metadata encryption. But all of these approaches have weaknesses (eg trust issues, the existence of a central point of attack, susceptibility to traffic analysis), and as long as Alice's messages are ultimately being delivered to Bob (and vice versa), then any adversary who could discover this would know that Alice and Bob were in communication. But what if Alice sent her encrypted messages not only to Bob, but to everyone ( * )? And everyone received them ( ** )? Public key encryption would ensure that only Bob would be able to actually decrypt and read the message, and meanwhile even an adversary with complete access to the entire network between Alice's and Bob's machines would still be unable to determine which particular instance of 'everyone' was the intended recipient. In other words, from the outside, an adversary would not be able to determine who Alice was talking to. ( * ) 'Everyone' here means 'everyone who's participating in this protocol'. Obviously, as with TOR, the more participants the better. This protocol would be trivially useless with only two users. But even three users would provide some protection. (Is Alice talking to Bob or to Carol?) And it would work a whole lot better if Bob were literally one in a million. ( ** ) Or rather: everyone's machine/device automatically received them. Each machine/device would then attempt to decrypt all incoming messages, and non-decipherable messages would automatically be discarded(***). The user would only be notified if the message was in fact for them. (***) Or, more efficiently, be forwarded to a swarm of peers in a process that would be analogous to seeding a torrent. If widely adopted, a protocol like this would presumably generate an insane amount of network traffic. Perhaps it might place an impossible, exponentially growing burden on the internet's infrastructure? I dunno. I also don't know if this could be mitigated by having each message be 'broadcast' using a P2P-like protocol? In any case, it's also going to be very resource intensive for every participating machine/device -- but then again, doesn't everyone who isn't mining bitcoins usually have countless unused CPU cycles on their machines? Speaking of massive waste... you could also use this protocol to conceal the identity of the sender if everyone's device was set to automatically generate and send out a continual stream of dummy encrypted messages. And again, perhaps the absolute number of dummy messages could somehow be managed by recycling discarded messages back out into the swarm. (Even if this is possible, I think this kind of recycling would have to be done carefully, but I don't want to get into the details here.) So what do you guys think? Is it so crazy it just might work? Or just plain crazy? Am I mischaracterizing the problem or the solution or missing some really obvious flaw?
Abstract As the most successful cryptocurrency to date, Bitcoin constitutes a target of choice for attackers. While many attack vectors have already been uncovered, one important vector has been left out though: attacking the currency via the Internet routing infrastructure itself. Indeed, by manipulating routing advertisements (BGP hijacks) or by naturally intercepting traffic, Autonomous Systems (ASes) can intercept and manipulate a large fraction of Bitcoin traffic. This paper presents the first taxonomy of routing attacks and their impact on Bitcoin, considering both small-scale attacks, targeting individual nodes, and large-scale attacks, targeting the network as a whole. While challenging, we show that two key properties make routing attacks practical: (i) the efficiency of routing manipulation; and (ii) the significant centralization of Bitcoin in terms of mining and routing. Specifically, we find that any network attacker can hijack few (<100) BGP prefixes to isolate ~50% of the mining power---even when considering that mining pools are heavily multi-homed. We also show that on-path network attackers can considerably slow down block propagation by interfering with few key Bitcoin messages. We demonstrate the feasibility of each attack against the deployed Bitcoin software. We also quantify their effectiveness on the current Bitcoin topology using data collected from a Bitcoin supernode combined with BGP routing data. The potential damage to Bitcoin is worrying. By isolating parts of the network or delaying block propagation, attackers can cause a significant amount of mining power to be wasted, leading to revenue losses and enabling a wide range of exploits such as double spending. To prevent such effects in practice, we provide both short and long-term countermeasures, some of which can be deployed immediately. References  “A Next-Generation Smart Contract and Decentralized Application Platform ,” https://github.com/ethereum/wiki/wiki/White-Paper.  “Bitcoin Blockchain Statistics,” https://blockchain.info/.  “bitnodes,” https://bitnodes.21.co/.  “Bitnodes. Estimating the size of Bitcoin network,” https://bitnodes.21.co/.  “CAIDA Macroscopic Internet Topology Data Kit.” https://www.caida.org/data/internet-topology-data-kit/.  “Dyn Research. Pakistan hijacks YouTube.” http://research.dyn.com/2008/02/pakistan-hijacks-youtube-1/.  “FALCON,” http://www.falcon-net.org/.  “FIBRE,” http://bitcoinfibre.org/.  “Litecoin ,” https://litecoin.org.  “RIPE RIS Raw Data,” https://www.ripe.net/data-tools/stats/ris/ris-raw-data.  “Routeviews Prefix to AS mappings Dataset (pfx2as) for IPv4 and IPv6.” https://www.caida.org/data/routing/routeviews-prefix2as.xml.  “Scapy.” http://www.secdev.org/projects/scapy/.  “The Relay Network,” http://bitcoinrelaynetwork.org/.  “ZCash,” https://z.cash/.  A. M. Antonopoulos, “The bitcoin network,” in Mastering Bitcoin. O’Reilly Media, Inc., 2013, ch. 6.  H. Ballani, P. Francis, and X. Zhang, “A Study of Prefix Hijacking and Interception in the Internet,” ser. SIGCOMM ’07. New York, NY, USA: ACM, 2007, pp. 265–276.  A. Boldyreva and R. Lychev, “Provable Security of S-BGP and Other Path Vector Protocols: Model, Analysis and Extensions,” ser. CCS ’12. New York, NY, USA: ACM, 2012, pp. 541–552.  J. Bonneau, A. Miller, J. Clark, A. Narayanan, J. A. Kroll, and E. W. Felten, “Sok: Research perspectives and challenges for bitcoin and cryptocurrencies,” in Security and Privacy (SP), 2015 IEEE Symposium on. IEEE, 2015, pp. 104–121.  P. Bosshart, D. Daly, G. Gibb, M. Izzard, N. McKeown, J. Rexford, C. Schlesinger, D. Talayco, A. Vahdat, G. Varghese et al., “P4: Programming protocol-independent packet processors,” ACM SIGCOMM Computer Communication Review, vol. 44, no. 3, pp. 87–95, 2014.  C. Decker and R. Wattenhofer, “Information propagation in the bitcoin network,” in Peer-to-Peer Computing (P2P), 2013 IEEE Thirteenth International Conference on. IEEE, 2013, pp. 1–10.  ——, Bitcoin Transaction Malleability and MtGox. Cham: Springer International Publishing, 2014, pp. 313–326. [Online]. Available: http://dx.doi.org/10.1007/978-3-319-11212-1_18  M. Edman and P. Syverson, “As-awareness in tor path selection,” in Proceedings of the 16th ACM Conference on Computer and Communications Security, ser. CCS ’09, 2009.  I. Eyal, “The miner’s dilemma,” in 2015 IEEE Symposium on Security and Privacy. IEEE, 2015, pp. 89–103.  I. Eyal and E. G. Sirer, “Majority is not enough: Bitcoin mining is vulnerable,” in Financial Cryptography and Data Security. Springer, 2014, pp. 436–454.  N. Feamster and R. Dingledine, “Location diversity in anonymity networks,” in WPES, Washington, DC, USA, October 2004.  J. Garay, A. Kiayias, and N. Leonardos, “The bitcoin backbone protocol: Analysis and applications,” in Advances in Cryptology-EUROCRYPT 2015. Springer, 2015, pp. 281–310.  A. Gervais, G. O. Karama, V. Capkun, and S. Capkun, “Is bitcoin a decentralized currency?” IEEE security & privacy, vol. 12, no. 3, pp. 54–60, 2014.  A. Gervais, H. Ritzdorf, G. O. Karame, and S. Capkun, “Tampering with the delivery of blocks and transactions in bitcoin,” in Proceedings of the 22Nd ACM SIGSAC Conference on Computer and Communications Security, ser. CCS ’15. New York, NY, USA: ACM, 2015, pp. 692–705.  P. Gill, M. Schapira, and S. Goldberg, “Let the Market Drive Deployment: A Strategy for Transitioning to BGP Security,” ser. SIGCOMM ’11. New York, NY, USA: ACM, 2011, pp. 14–25.  S. Goldberg, M. Schapira, P. Hummon, and J. Rexford, “How Secure Are Secure Interdomain Routing Protocols,” in SIGCOMM, 2010.  E. Heilman, A. Kendler, A. Zohar, and S. Goldberg, “Eclipse attacks on bitcoin’s peer-to-peer network,” in 24th USENIX Security Symposium (USENIX Security 15), 2015, pp. 129–144.  Y.-C. Hu, A. Perrig, and M. Sirbu, “SPV: Secure Path Vector Routing for Securing BGP,” ser. SIGCOMM ’04. New York, NY, USA: ACM, 2004, pp. 179–192.  J. Karlin, S. Forrest, and J. Rexford, “Pretty Good BGP: Improving BGP by Cautiously Adopting Routes,” in Proceedings of the Proceedings of the 2006 IEEE International Conference on Network Protocols, ser. ICNP ’06. Washington, DC, USA: IEEE Computer Society, 2006, pp. 290–299.  E. K. Kogias, P. Jovanovic, N. Gailly, I. Khoffi, L. Gasser, and B. Ford, “Enhancing bitcoin security and performance with strong consistency via collective signing,” in 25th USENIX Security Symposium (USENIX Security 16). Austin, TX: USENIX Association, 2016, pp. 279–296.  J. A. Kroll, I. C. Davey, and E. W. Felten, “The economics of bitcoin mining, or bitcoin in the presence of adversaries.” Citeseer.  A. Miller, J. Litton, A. Pachulski, N. Gupta, D. Levin, N. Spring, and B. Bhattacharjee, “Discovering bitcoin’s public topology and influential nodes.”  S. J. Murdoch and P. Zielinski, “Sampled traffic analysis by Internet- ´ exchange-level adversaries,” in Privacy Enhancing Technologies: 7th International Symposium, PET 2007, N. Borisov and P. Golle, Eds. Springer-Verlag, LNCS 4776, 2007, pp. 167–183.  K. Nayak, S. Kumar, A. Miller, and E. Shi, “Stubborn mining: Generalizing selfish mining and combining with an eclipse attack,” IACR Cryptology ePrint Archive, vol. 2015, p. 796, 2015.  T. Neudecker, P. Andelfinger, and H. Hartenstein, “A simulation model for analysis of attacks on the bitcoin peer-to-peer network,” in IFIP/IEEE International Symposium on Internet Management. IEEE, 2015, pp. 1327–1332.  P. v. Oorschot, T. Wan, and E. Kranakis, “On interdomain routing security and pretty secure bgp (psbgp),” ACM Trans. Inf. Syst. Secur., vol. 10, no. 3, Jul. 2007.  A. Pilosov and T. Kapela, “Stealing The Internet. An Internet-Scale Man In The Middle Attack.” DEFCON 16.  Y. Rekhter and T. Li, A Border Gateway Protocol 4 (BGP-4), IETF, Mar. 1995, rFC 1771.  M. Rosenfeld, “Analysis of hashrate-based double spending,” arXiv preprint arXiv:1402.2009, 2014.  A. Sapirshtein, Y. Sompolinsky, and A. Zohar, “Optimal selfish mining strategies in bitcoin,” CoRR, vol. abs/1507.06183, 2015.  E. B. Sasson, A. Chiesa, C. Garman, M. Green, I. Miers, E. Tromer, and M. Virza, “Zerocash: Decentralized anonymous payments from bitcoin,” in 2014 IEEE Symposium on Security and Privacy. IEEE, 2014, pp. 459–474.  B. Schlinker, K. Zarifis, I. Cunha, N. Feamster, and E. Katz-Bassett, “Peering: An as for us,” in Proceedings of the 13th ACM Workshop on Hot Topics in Networks, ser. HotNets-XIII. New York, NY, USA: ACM, 2014, pp. 18:1–18:7.  J. Schnelli, “BIP 151: Peer-to-Peer Communication Encryption,” Mar. 2016, https://github.com/bitcoin/bips/blob/mastebip-0151.mediawiki.  X. Shi, Y. Xiang, Z. Wang, X. Yin, and J. Wu, “Detecting prefix hijackings in the Internet with Argus,” ser. IMC ’12. New York, NY, USA: ACM, 2012, pp. 15–28.  Y. Sompolinsky and A. Zohar, “Secure high-rate transaction processing in bitcoin,” in Financial Cryptography and Data Security. Springer, 2015, pp. 507–527.  Y. Sun, A. Edmundson, L. Vanbever, O. Li, J. Rexford, M. Chiang, and P. Mittal, “RAPTOR: Routing attacks on privacy in TOR.” in USENIX Security, 2015.  A. Tonk, “Large scale BGP hijack out of India,” 2015, http://www.bgpmon.net/large-scale-bgp-hijack-out-of-india/.  ——, “Massive route leak causes Internet slowdown,” 2015, http://www.bgpmon.net/massive-route-leak-cause-internet-slowdown/.  L. Vanbever, O. Li, J. Rexford, and P. Mittal, “Anonymity on quicksand: Using BGP to compromise TOR,” in ACM HotNets, 2014.  Z. Zhang, Y. Zhang, Y. C. Hu, and Z. M. Mao, “Practical defenses against BGP prefix hijacking,” ser. CoNEXT ’07. New York, NY, USA: ACM, 2007.  Z. Zhang, Y. Zhang, Y. C. Hu, Z. M. Mao, and R. Bush, “iSPY: Detecting IP prefix hijacking on my own,” IEEE/ACM Trans. Netw., vol. 18, no. 6, pp. 1815–1828, Dec. 2010.
An Analysis of Anonymity in Bitcoin Using P2P Network Tra c Philip Koshy, Diana Koshy, and Patrick McDaniel Pennsylvania State University, University Park, PA 16802, USA Abstract. Over the last 4 years, Bitcoin, a decentralized P2P crypto-currency, has gained widespread attention. The ability to create pseudo- Koshy P., Koshy D., McDaniel P. (2014) An Analysis of Anonymity in Bitcoin Using P2P Network Traffic. In: Christin N., Safavi-Naini R. (eds) Financial Cryptography and Data Security. FC 2014. Download Citation | An Analysis of Anonymity in Bitcoin Using P2P Network Traffic | Over the last 4 years, Bitcoin, a decentralized P2P crypto-currency, has gained widespread attention. The Bitcoin has attracted considerable attention from governments, banks, as well as researchers. However, Bitcoin is not a completely anonymous system. All transaction information in the Bitcoin system is published on the network and can be used to reveal the identity of the user by transaction correlation analysis. In this paper, a secure and privacy-preserving mix service for Bitcoin anonymity Over the last 4 years, Bitcoin, a decentralized P2P crypto-currency, has gained widespread attention. The ability to create pseudo-anonymous financial transactions using bitcoins has made the currency attractive to users who value their privacy. Although previous work has analyzed the degree of anonymity Bitcoin offers using clustering and flow analysis, none have demonstrated the ability to
A superior alternative emerged with the birth of Bitcoin; trustless p2p electronic cash that’s independent of central banks, governments, or any other centralized middle-men. Transactions in bitcoin form a publicly accessible network of economic relations, which can be extracted from the transaction history available to all users in the P2P-network of bitcoin. Using re ... Videos of talks and presentations from the 25th ACM Conference on Computer and Communications Security will be held in Toronto, Canada from October 15, 2018 to October 19, 2018. Riposte is the first such system, to our knowledge, that simultaneously protects against traffic-analysis attacks, prevents anonymous denial-of-service by malicious clients, and scales to million ... Utopia – это революционная децентрализованная P2P экосистема без центрального сервера ...