Sourav Das (Department of Computer Science and Engineering, Indian Institute of Technology Delhi), Vinay Joseph Ribeiro (Department of Computer Science and Engineering, Indian Institute of Technology Delhi), Abhijeet Anand (Department of Computer Science and Engineering, Indian Institute of Technology Delhi)

One major shortcoming of permissionless blockchains such as Bitcoin and Ethereum is that they are unsuitable for running Computationally Intensive smart Contracts (CICs). This prevents such blockchains from running Machine Learning algorithms, Zero-Knowledge proofs, etc. which may need non-trivial computation.

In this paper, we present YODA, which is to the best of our knowledge the first solution for efficient computation of CICs in permissionless blockchains with guarantees for a threat model with both Byzantine and selfish nodes. YODA selects one or more execution sets (ES) via Sortition to execute a particular CIC off-chain. One key innovation is the MultI-Round Adaptive Consensus using Likelihood Estimation (MiRACLE) algorithm based on sequential hypothesis testing. MiRACLE allows the execution sets to be small thus making YODA efficient while ensuring correct CIC execution with high probability. It adapts the number of ES sets automatically depending on the concentration of Byzantine nodes in the system and is optimal in terms of the expected number of ES sets used in certain scenarios. Through a suite of economic incentives and technical mechanisms such as the novel Randomness Inserted Contract Execution (RICE) algorithm, we force selfish nodes to behave honestly. We also prove that the honest behavior of selfish nodes is an approximate Nash Equilibrium. We present the system design and details of YODA and prove the security properties of MiRACLE and RICE. Our prototype implementation built on top of Ethereum demonstrates the ability of YODA to run CICs with orders of magnitude higher gas per unit time as well as total gas requirements than Ethereum currently supports. It also demonstrates the low overheads of RICE.

View More Papers

Statistical Privacy for Streaming Traffic

Xiaokuan Zhang (The Ohio State University), Jihun Hamm (The Ohio State University), Michael K. Reiter (University of North Carolina at Chapel Hill), Yinqian Zhang (The Ohio State University)

Read More

Geo-locating Drivers: A Study of Sensitive Data Leakage in...

Qingchuan Zhao (The Ohio State University), Chaoshun Zuo (The Ohio State University), Giancarlo Pellegrino (CISPA, Saarland University; Stanford University), Zhiqiang Lin (The Ohio State University)

Read More

UWB with Pulse Reordering: Securing Ranging against Relay and...

Mridula Singh (ETH Zurich, Switzerland), Patrick Leu (ETH Zurich, Switzerland), Srdjan Capkun (ETH Zurich, Switzerland)

Read More

Understanding Open Ports in Android Applications: Discovery, Diagnosis, and...

Daoyuan Wu (Singapore Management University), Debin Gao (Singapore Management University), Rocky K. C. Chang (The Hong Kong Polytechnic University), En He (China Electronic Technology Cyber Security Co., Ltd.), Eric K. T. Cheng (The Hong Kong Polytechnic University), Robert H. Deng (Singapore Management University)

Read More