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School of Computer Science Technical Report Series

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Author: Carter, Henry × Author: Traynor, Patrick × Item Type: Publication ×

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    Whitewash: Outsourcing Garbled Circuit Generation for Mobile Devices
    (Georgia Institute of Technology, 2014) Carter, Henry ; Lever, Charles ; Traynor, Patrick
    Garbled circuits offer a powerful primitive for computation on a user’s personal data while keeping that data private. Despite recent improvements, constructing and evaluating circuits of any useful size remains expensive on the limited hardware resources of a smartphone, the primary computational device available to most users around the world. In this work, we develop a new technique for securely outsourcing the generation of garbled circuits to a Cloud provider. By outsourcing the circuit generation, we are able to eliminate the most costly operations from the mobile device, including oblivious transfers. After proving the security of our techniques in the malicious model, we experimentally demonstrate that our new protocol, built on this role reversal, decreases execution time by 98% and reduces network costs by as much as 63% compared to previous outsourcing protocols. In so doing, we demonstrate that the use of garbled circuits on mobile devices can be made nearly as practical as it is becoming for server-class machines.
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    Secure Outsourced Garbled Circuit Evaluation for Mobile Devices
    (Georgia Institute of Technology, 2012) Carter, Henry ; Mood, Benjamin ; Traynor, Patrick ; Butler, Kevin
    Garbled circuits provide a powerful tool for jointly evaluating functions while preserving the privacy of each user’s inputs. While recent research has made the use of this primitive more practical, such solutions generally assume that participants are symmetrically provisioned with massive computing resources. In reality, most people on the planet only have access to the comparatively sparse computational resources associated with their mobile phones, and those willing and able to pay for access to public cloud computing infrastructure cannot be assured that their data will remain unexposed. We address this problem by creating a new SFE protocol that allows mobile devices to securely outsource the majority of computation required to evaluate a garbled circuit. Our protocol, which builds on the most efficient garbled circuit evaluation techniques, includes a new outsourced oblivious transfer primitive that requires significantly less bandwidth and computation than standard OT primitives and outsourced input validation techniques that force the cloud to prove that it is executing all protocols correctly. After showing that our extensions are secure in the malicious model, we conduct an extensive performance evaluation for a number of standard SFE test applications as well as a privacy-preserving navigation application designed specifically for the mobile use-case. Our system reduces execution time by 98.92% and bandwidth by 99.95% for the edit distance problem of size 128 compared to non-outsourced evaluation. These results show that even the least capable devices are capable of evaluating some of the largest garbled circuits generated for any platform.
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    Efficient Oblivious Computation Techniques for Privacy-Preserving Mobile Applications
    (Georgia Institute of Technology, 2011) Carter, Henry ; Amrutkar, Chaitrali ; Dacosta, Italo ; Traynor, Patrick
    The growth of smartphone capability has led to an explosion of new applications. Many of the most useful apps use context-sensitive data, such as GPS location or social network information. In these cases, users may not be willing to release personal information to untrusted parties. Currently, the solutions to performing computation on encrypted inputs use garbled circuits combined with a variety of optimizations. However, the capability of resource-constrained smartphones for evaluating garbled circuits in any variation is uncertain in practice. In [1], it is shown that certain garbled circuit evaluations can be optimized by using homomorphic encryption. In this paper, we take this concept to its logical extreme with Efficient Mobile Oblivious Computation (EMOC), a technique that completely replaces garbled circuits with homomorphic operations on ciphertexts. We develop applications to securely solve the millionaire’s problem, send tweets based on location, and compute common friends in a social network, then prove equivalent privacy guarantees to analogous constructions using garbled circuits. We then demonstrate up to 68% runtime reduction from the most efficient garbled circuit implementation. In so doing, we demonstrate a practical technique for developing privacy-preserving applications on the mobile platform.