Abstract
Proof-of-Work (PoW) based blockchains typically allocate only a tiny fraction (e.g., less than 1% for Ethereum) of the average interarrival time (I) between blocks for validating smart contracts present in transactions. In such systems, block validation and PoW mining are typically performed sequentially, the former by CPUs and the latter by ASICs. A trivial increase in validation time (τ) introduces the popularly known Verifier's Dilemma, and as we demonstrate, causes more forking and hurts fairness. Large τ also reduces the tolerance for safety against a Byzantine adversary. Solutions that offload validation to a set of non-chain nodes (a.k.a. off-chain approaches) suffer from trust and performance issues that are non-trivial to resolve. In this paper, we present Tuxedo, the first on-chain protocol to theoretically scale τ/I ≈1 in PoW blockchains. The key innovation in Tuxedo is to perform CPU-based block processing in parallel to ASIC mining. We achieve this by allowing miners to delay validation of transactions in a block by up to ζ blocks, where ζ is a system parameter. We perform security analysis of Tuxedo considering all possible adversarial strategies in a synchronous network with maximum end-to-end delay Δ and demonstrate that Tuxedo achieves security equivalent to known results for longest chain PoW Nakamoto consensus. Our prototype implementation of Tuxedo atop Ethereum demonstrates that it can scale τ without suffering the harmful effects of naive scaling up of τ/I in existing blockchains
- Mustafa Al-Bassam, Alberto Sonnino, Shehar Bano, Dave Hrycyszyn, and George Danezis. 2018. Chainspace: A Sharded Smart Contract Platform. In Network and Distributed System Security Symposium 2018 (NDSS 2018) .Google Scholar
- Parwat Singh Anjana, Sweta Kumari, Sathya Peri, Sachin Rathor, and Archit Somani. 2018. An Efficient Framework for Concurrent Execution of Smart Contracts. CoRR , Vol. abs/1809.01326 (2018). arxiv: 1809.01326 http://arxiv.org/abs/1809.01326Google Scholar
- Sean Bowe, Alessandro Chiesa, Matthew Green, Ian Miers, Pratyush Mishra, and Howard Wu. 2020. Zexe: Enabling decentralized private computation. In 2020 IEEE Symposium on Security and Privacy (SP). IEEE, 947--964.Google Scholar
Cross Ref
- Ferdinand Brasser, Urs Müller, Alexandra Dmitrienko, Kari Kostiainen, Srdjan Capkun, and Ahmad-Reza Sadeghi. 2017. Software grand exposure:SGX cache attacks are practical. In 11th USENIX Workshop on Offensive Technologies (WOOT 17) .Google Scholar
- Raymond Cheng, Fan Zhang, Jernej Kos, Warren He, Nicholas Hynes, Noah Johnson, Ari Juels, Andrew Miller, and Dawn Song. 2019. Ekiden: A platform for confidentiality-preserving, trustworthy, and performant smart contracts. In 2019 IEEE European Symposium on Security and Privacy (EuroS&P). IEEE, 185--200.Google Scholar
Cross Ref
- Alexander Chepurnoy, Charalampos Papamanthou, and Yupeng Zhang. 2018. Edrax: A Cryptocurrency with Stateless Transaction Validation. (2018).Google Scholar
- Sourav Das, Vinay Joseph Ribeiro, and Abhijeet Anand. 2019. YODA: Enabling computationally intensive contracts on blockchains with Byzantine and Selfish nodes. In Proceedings of the 26th Annual Network and Distributed System Security Symposium .Google Scholar
Cross Ref
- Amir Dembo, Sreeram Kannan, Ertem Nusret Tas, David Tse, Pramod Viswanath, Xuechao Wang, and Ofer Zeitouni. 2020. Everything is a race and Nakamoto always wins. In Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security. 859--878.Google Scholar
Digital Library
- Thomas Dickerson, Paul Gazzillo, Maurice Herlihy, and Eric Koskinen. 2017. Adding Concurrency to Smart Contracts. In Proceedings of the ACM Symposium on Principles of Distributed Computing (PODC '17). 303--312.Google Scholar
Digital Library
- Jacob Eberhardt and Stefan Tai. 2018. ZoKrates-Scalable Privacy-Preserving Off-Chain Computations. In IEEE International Conference on Blockchain .Google Scholar
- Juan Garay, Aggelos Kiayias, and Nikos Leonardos. 2015. The bitcoin backbone protocol: Analysis and applications. In Annual International Conference on the Theory and Applications of Cryptographic Techniques. Springer, 281--310.Google Scholar
Cross Ref
- Peter Gavz i, Aggelos Kiayias, and Alexander Russell. 2020. Tight consistency bounds for bitcoin. In Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security. 819--838.Google Scholar
- Adem Efe Gencer, Soumya Basu, Ittay Eyal, Robbert Van Renesse, and Emin Gün Sirer. 2018. Decentralization in bitcoin and ethereum networks. In International Conference on Financial Cryptography and Data Security. Springer, 439--457.Google Scholar
Digital Library
- Harry Kalodner, Steven Goldfeder, Xiaoqi Chen, S Matthew Weinberg, and Edward W Felten. 2018. Arbitrum: Scalable, private smart contracts. In 27th USENIX Security Symposium (USENIX Security 18). 1353--1370.Google Scholar
- Lucianna Kiffer, Rajmohan Rajaraman, et almbox. 2018. A better method to analyze blockchain consistency. In Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security. ACM, 729--744.Google Scholar
Digital Library
- Eleftherios Kokoris-Kogias, Philipp Jovanovic, Linus Gasser, Nicolas Gailly, Ewa Syta, and Bryan Ford. 2018. Omniledger: A secure, scale-out, decentralized ledger via sharding. In 2018 IEEE Symposium on Security and Privacy (SP). IEEE, 583--598.Google Scholar
Cross Ref
- Jonathan Lee, Kirill Nikitin, and Srinath Setty. 2020. Replicated state machines without replicated execution. In 2020 IEEE Symposium on Security and Privacy (SP). IEEE, 119--134.Google Scholar
Cross Ref
- Loi Luu, Viswesh Narayanan, Chaodong Zheng, Kunal Baweja, Seth Gilbert, and Prateek Saxena. 2016. A secure sharding protocol for open blockchains. In Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security. ACM, 17--30.Google Scholar
Digital Library
- Loi Luu, Jason Teutsch, Raghav Kulkarni, and Prateek Saxena. 2015. Demystifying incentives in the consensus computer. In Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security. ACM, 706--719.Google Scholar
Digital Library
- Ujan Mukhopadhyay, Anthony Skjellum, Oluwakemi Hambolu, Jon Oakley, Lu Yu, and Richard Brooks. 2016. A brief survey of Cryptocurrency systems. In 2016 14th Annual Conference on Privacy, Security and Trust (PST). 745--752. https://doi.org/10.1109/PST.2016.7906988Google Scholar
Cross Ref
- Satoshi Nakamoto et almbox. 2008. Bitcoin: A peer-to-peer electronic cash system. (2008).Google Scholar
- Ilkka Norros. 1994. A storage model with self-similar input. Queueing systems , Vol. 16, 3--4 (1994), 387--396.Google Scholar
- Rafael Pass, Lior Seeman, and Abhi Shelat. 2017. Analysis of the blockchain protocol in asynchronous networks. In Annual International Conference on the Theory and Applications of Cryptographic Techniques. Springer, 643--673.Google Scholar
Cross Ref
- Ling Ren. 2019. Analysis of Nakamoto Consensus. Cryptology ePrint Archive, Report 2019/943. https://eprint.iacr.org/2019/943.Google Scholar
- Hubert Ritzdorf, Karl Wüst, Arthur Gervais, Guillaume Felley, and Srdjan Capkun. 2018. TLS-N: non-repudiation over TLS enabling ubiquitous content signing for disintermediation. In Proceedings of the 25th Annual Network and Distributed System Security Symposium .Google Scholar
Cross Ref
- Pingcheng Ruan, Tien Tuan Anh Dinh, Dumitrel Loghin, Meihui Zhang, Gang Chen, Qian Lin, and Beng Chin Ooi. 2021. Blockchains vs. Distributed Databases: Dichotomy and Fusion. In Proceedings of the 2021 International Conference on Management of Data . 1504--1517.Google Scholar
Digital Library
- John G Skellam. 1946. The frequency distribution of the difference between two Poisson variates belonging to different populations. Journal of the Royal Statistical Society. Series A (General) , Vol. 109, Pt 3 (1946), 296--296.Google Scholar
- Jason Teutsch and Christian Reitwießner. 2017. A scalable verification solution for blockchains. (2017).Google Scholar
- Alin Tomescu, Ittai Abraham, Vitalik Buterin, Justin Drake, Dankrad Feist, and Dmitry Khovratovich. 2020. Aggregatable subvector commitments for stateless cryptocurrencies. In International Conference on Security and Cryptography for Networks. Springer, 45--64.Google Scholar
Digital Library
- Jo Van Bulck, Marina Minkin, Ofir Weisse, Daniel Genkin, Baris Kasikci, Frank Piessens, Mark Silberstein, Thomas F Wenisch, Yuval Yarom, and Raoul Strackx. 2018. Foreshadow: Extracting the keys to the intel SGX kingdom with transient out-of-order execution. In 27th USENIX Security Symposium (USENIX Security 18). 991--1008.Google Scholar
Digital Library
- Jiaping Wang and Hao Wang. 2019. Monoxide: Scale out Blockchains with Asynchronous Consensus Zones. In 16th USENIX Symposium on Networked Systems Design and Implementation (NSDI 19) . 95--112.Google Scholar
- Karl Wüst, Sinisa Matetic, Silvan Egli, Kari Kostiainen, and Srdjan Capkun. 2020. ACE: Asynchronous and concurrent execution of complex smart contracts. In Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security . 587--600.Google Scholar
Digital Library
- Mahdi Zamani, Mahnush Movahedi, and Mariana Raykova. 2018. Rapidchain: Scaling blockchain via full sharding. In Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security. ACM, 931--948.Google Scholar
Digital Library
- An Zhang and Kunlong Zhang. 2018. Enabling concurrency on smart contracts using multiversion ordering. In Asia-Pacific Web (APWeb) and Web-Age Information Management (WAIM) Joint International Conference on Web and Big Data. Springer, 425--439.Google Scholar
Cross Ref
Index Terms
Tuxedo: Maximizing Smart Contract Computation in PoW Blockchains
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