Publications

Abstract not provided.

Simple but mission-critical internet-based applications that require extremely high reliability, availability, and verifiability (e.g., auditability) could benefit from running on robust public programmable blockchain platforms such as Ethereum. Unfortunately, program code running on such blockchains is normally publicly viewable, rendering these platforms unsuitable for applications requiring strict privacy of application code, data, and results. In this work, we investigate using MPC techniques to protect the privacy of a blockchain computation. While our main goal is to hide both the data and the computed function itself, we also consider the standard MPC setting where the function is public. We describe GABLE (Garbled Autonomous Bots Leveraging Ethereum), a blockchain MPC architecture and system. The GABLE architecture specifies the roles and capabilities of the players. GABLE includes two approaches for implementing MPC over blockchain: Garbled Circuits (GC), evaluating universal circuits, and Garbled Finite State Automata (GFSA). We formally model and prove the security of GABLE implemented over garbling schemes, a popular abstraction of GC and GFSA from (Bellare et al., CCS 2012). We analyze in detail the performance (including Ethereum gas costs) of both approaches and discuss the trade-offs. We implement a simple prototype of GABLE and report on the implementation issues and experience.

Simple but mission-critical internet-based applications that require extremely high reliability and availability could potentially benefit from running on robust public programmable blockchain platforms such as Ethereum. Unfortunately, program code running on such blockchains is ordinarily publicly viewable, rendering these platforms unsuitable for applications requiring strict privacy of application code, data, and results. However, might it be possible to encode an application's business logic and data for these platforms in such a way that it becomes impossible for unauthorized parties to infer any meaningful information whatsoever about the semantics of the data, and the operations being performed on that data? In this report, we describe GABLE (Garbled Autonomous Bots Leveraging Ethereum), a system concept developed at Sandia that achieves this security goal in a limited, but still useful range of circumstances. GABLE, uses simple but effective algorithms to permit secure private execution of garbled state machines (and more efficient garbled circuits) on public computing resources. We give an example working implementation for garbled state machines, written using the Python and Solidity programming languages, and outline how our methods can be extended to support a more powerful garbled universal circuit model of computation. The capability embodied by the GABLE, system has significant potential applications, a few of which we discuss in this report.