Judmayer, A., Stifter, N., Zamyatin, A., Tsabary, I., Eyal, I., Gaži, P., Meiklejohn, S., & Weippl, E. (2021). Pay to Win: Cheap, Cross-Chain Bribing Attacks on PoW Cryptocurrencies. In Financial Cryptography and Data Security. FC 2021 International Workshops (pp. 533–549). Springer. https://doi.org/10.1007/978-3-662-63958-0_39
In this paper we extend the attack landscape of bribing attacks on cryptocurrencies by presenting a new method, which we call Pay-To-Win (P2W). To the best of our knowledge, it is the first approach capable of facilitating double-spend collusion across different blockchains. Moreover, our technique can also be used to specifically incentivize transaction exclusion or (re)ordering. For our construction we rely on smart contracts to render the payment and receipt of bribes trustless for the briber as well as the bribee. Attacks using our approach are operated and financed out-of-band i.e., on a funding cryptocurrency, while the consequences are induced in a different target cryptocurrency. Hereby, the main requirement is that smart contracts on the funding cryptocurrency are able to verify consensus rules of the target. For a concrete instantiation of our P2W method, we choose Bitcoin as a target and Ethereum as a funding cryptocurrency. Our P2W method is designed in a way that reimburses collaborators even in the case of an unsuccessful attack. Interestingly, this actually renders our approach approximately one order of magnitude cheaper than comparable bribing techniques (e.g., the whale attack). We demonstrate the technical feasibility of P2W attacks through publishing all relevant artifacts of this paper, ranging from calculations of success probabilities to a fully functional proof-of-concept implementation, consisting of an Ethereum smart contract and a Python client.
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Project title:
Verbesserung der Sicherheit von Informationsprozessen in Produktionssystemen: CDL SQI (CDG Christian Doppler Forschungsgesellschaft; CDG Christian Doppler Forschungsgesellschaft)
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Project (external):
Austrian Federal Ministry for Digital and Economic Affairs Nation Foundation for Research, Technology and Development FFG
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Project ID:
864738 PR4DLT
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Research Areas:
Computer Engineering and Software-Intensive Systems: 50% Information Systems Engineering: 50%