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

DIAT: Data Integrity Attestation for Resilient Collaboration of Autonomous...

Tigist Abera (Technische Universität Darmstadt), Raad Bahmani (Technische Universität Darmstadt), Ferdinand Brasser (Technische Universität Darmstadt), Ahmad Ibrahim (Technische Universität Darmstadt), Ahmad-Reza Sadeghi (Technische Universität Darmstadt), Matthias Schunter (Intel Labs)

Read More

Unveiling your keystrokes: A Cache-based Side-channel Attack on Graphics...

Daimeng Wang (University of California Riverside), Ajaya Neupane (University of California Riverside), Zhiyun Qian (University of California Riverside), Nael Abu-Ghazaleh (University of California Riverside), Srikanth V. Krishnamurthy (University of California Riverside), Edward J. M. Colbert (Virginia Tech), Paul Yu (U.S. Army Research Lab (ARL))

Read More

Neuro-Symbolic Execution: Augmenting Symbolic Execution with Neural Constraints

Shiqi Shen (National University of Singapore), Shweta Shinde (National University of Singapore), Soundarya Ramesh (National University of Singapore), Abhik Roychoudhury (National University of Singapore), Prateek Saxena (National University of Singapore)

Read More

PeriScope: An Effective Probing and Fuzzing Framework for the...

Dokyung Song (University of California, Irvine), Felicitas Hetzelt (Technical University of Berlin), Dipanjan Das (University of California, Santa Barbara), Chad Spensky (University of California, Santa Barbara), Yeoul Na (University of California, Irvine), Stijn Volckaert (University of California, Irvine and KU Leuven), Giovanni Vigna (University of California, Santa Barbara), Christopher Kruegel (University of California, Santa Barbara),…

Read More