Publications

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, 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.

Recent research and development in exploiting quantum phenomenon have solidified the creation of large-scale quantum computers as a reality. These machines will have the ability to solve intractable problems defined on conventional computers. This has a significant impact on current cryptographic systems. A viable quantum computer will require an increase in symmetric key sizes and the replacement of asymmetric cryptographic schemes. Specifically, new constructs for public key cryptosystems must be established in order to continue to ensure the security that digital signatures and key exchange protocols provide. Understanding the post-quantum landscape is critical to applying Sandia-developed capabilities to post-quantum cyber areas. Developing a cohort of experts in this challenging and volatile space has enabled our ability to adapt to the new challenges in various customer mission areas.

As a tool developed to translate geospatial data into geometrical descriptors, Tracktable offers a highly efficient means to detect anomalous flight and maritime behavior. Following the success of using geometrical descriptors for detecting anomalous trajectory behavior, the question of whether Tracktable could be used to detect satellite maneuvers arose. In answering this question, this re- port will introduce a brief description of how Tracktable has been used in the past, along with an introduction to the fundamental properties of astrodynamics for satellite trajectories. This will then allow us to compare the two problem spaces, addressing how easily the methods used by Tracktable will translate to orbital mechanics. Based on these results, we will then be able to out- line the current limitations as well as possible path forward for using Tracktable to detect satellite maneuvers.