Karl Wüst (ETH Zurich), Loris Diana (ETH Zurich), Kari Kostiainen (ETH Zurich), Ghassan Karame (NEC Labs), Sinisa Matetic (ETH Zurich), Srdjan Capkun (ETH Zurich)

In this paper we propose Bitcontracts, a novel solution that enables secure and efficient execution of generic smart contracts on top of unmodified legacy cryptocurrencies like Bitcoin that do not support contracts natively. The starting point of our solution is an off-chain execution model, where the contract's issuers appoints a set of service providers to execute the contract's code. The contract's execution results are accepted if a quorum of service providers reports the same result and clients are free to choose which such contracts they trust and use. The main technical contribution of this paper is how to realize such a trust model securely and efficiently without modifying the underlying blockchain.

We also identify a set of generic properties that a blockchain system must support so that expressive smart contracts can be added safely, and analyze popular existing blockchains based on these criteria.

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ROV++: Improved Deployable Defense against BGP Hijacking

Reynaldo Morillo (University of Connecticut), Justin Furuness (University of Connecticut), Cameron Morris (University of Connecticut), James Breslin (University of Connecticut), Amir Herzberg (University of Connecticut), Bing Wang (University of Connecticut)

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Practical Blind Membership Inference Attack via Differential Comparisons

Bo Hui (The Johns Hopkins University), Yuchen Yang (The Johns Hopkins University), Haolin Yuan (The Johns Hopkins University), Philippe Burlina (The Johns Hopkins University Applied Physics Laboratory), Neil Zhenqiang Gong (Duke University), Yinzhi Cao (The Johns Hopkins University)

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POSEIDON: Privacy-Preserving Federated Neural Network Learning

Sinem Sav (EPFL), Apostolos Pyrgelis (EPFL), Juan Ramón Troncoso-Pastoriza (EPFL), David Froelicher (EPFL), Jean-Philippe Bossuat (EPFL), Joao Sa Sousa (EPFL), Jean-Pierre Hubaux (EPFL)

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