5 research outputs found

    Perfectly Secure Oblivious Parallel RAM

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    We show that PRAMs can be obliviously simulated with perfect security, incurring only O(logNloglogN)O(\log N \log \log N) blowup in parallel runtime, O(log3N)O(\log^3 N) blowup in total work, and O(1)O(1) blowup in space relative to the original PRAM. Our results advance the theoretical understanding of Oblivious (Parallel) RAM in several respects. First, prior to our work, no perfectly secure Oblivious Parallel RAM (OPRAM) construction was known; and we are the first in this respect. Second, even for the sequential special case of our algorithm (i.e., perfectly secure ORAM), we not only achieve logarithmic improvement in terms of space consumption relative to the state-of-the-art but also significantly simplify perfectly secure ORAM constructions. Third, our perfectly secure OPRAM scheme matches the parallel runtime of earlier statistically secure schemes with negligible failure probability. Since we remove the dependence (in performance) on the security parameter, our perfectly secure OPRAM scheme in fact asymptotically outperforms known statistically secure ones if (sub-)exponentially small failure probability is desired. Our techniques for achieving small parallel runtime are novel and we employ expander graphs to de-randomize earlier statistically secure schemes --- this is the first time such techniques are used in the constructions of ORAMs/OPRAMs

    Efficient Data-Oblivious Computation

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    The rapid increase in the amount of data stored by cloud servers has resulted in growing privacy concerns for users. First, although keeping data encrypted at all times is an attractive approach to privacy, encryption may preclude mining and learning useful patterns from data. Second, companies are unable to distribute proprietary programs to other parties without risking the loss of their private code when those programs are reverse engineered. A challenge underlying both those problems is that how data is accessed — even when that data is encrypted — can leak secret information. Oblivious RAM is a well studied cryptographic primitive that can be used to solve the underlying challenge of hiding data-access patterns. In this dissertation, we improve Oblivious RAMs and oblivious algorithms asymptotically. We then show how to apply our novel oblivious algorithms to build systems that enable privacy-preserving computation on encrypted data and program obfuscation. Specifically, the first part of this dissertation shows two efficient Oblivious RAM algorithms: 1) The first algorithm achieves sub-logarithmic bandwidth blowup while only incurring an inexpensive XOR computation for performing Private Information Retrieval operations, and 2) The second algorithm is the first perfectly-secure Oblivious Parallel RAM with O(log3N)O(\log^3 N ) bandwidth blowup, O((logm+loglogN)logN)O((\log m + \log \log N)\log N) depth blowup, and O(1)O(1) space blowup when the PRAM has mm CPUs and stores NN blocks of data. The second part of this dissertation describes two systems — HOP and GraphSC — that address the problem of computing on private data and the distribution of proprietary programs. HOP is a system that achieves simulation-secure obfuscation of RAM programs assuming secure hardware. It is the first prototype implementation of a provably secure virtual black-box (VBB) obfuscation scheme in any model under any assumptions. GraphSC is a system that allows cloud servers to run a class of data-mining and machine-learning algorithms over users’ data without learning anything about that data. GraphSC brings efficient, parallel secure computation to programmers by allowing them to express computation tasks using the GraphLab abstraction. It is backed by the first non-trivial parallel oblivious algorithms that outperform generic Oblivious RAMs

    More is Less: Perfectly Secure Oblivious Algorithms in the Multi-Server Setting

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    The problem of Oblivious RAM (ORAM) has traditionally been studied in a single-server setting, but more recently the multi-server setting has also been considered. Yet it is still unclear whether the multi-server setting has any inherent advantages, e.g., whether the multi-server setting can be used to achieve stronger security goals or provably better efficiency than is possible in the single-server case. In this work, we construct a perfectly secure 3-server ORAM scheme that outperforms the best known single-server scheme by a logarithmic factor. In the process, we also show, for the first time, that there exist specific algorithms for which multiple servers can overcome known lower bounds in the single-server setting.Comment: 36 pages, Accepted in Asiacrypt 201

    Secure Massively Parallel Computation for Dishonest Majority

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    This work concerns secure protocols in the massively parallel computation (MPC) model, which is one of the most widely-accepted models for capturing the challenges of writing protocols for the types of parallel computing clusters which have become commonplace today (MapReduce, Hadoop, Spark, etc.). Recently, the work of Chan et al. (ITCS \u2720) initiated this study, giving a way to compile any MPC protocol into a secure one in the common random string model, achieving the standard secure multi-party computation definition of security with up to 1/3 of the parties being corrupt. We are interested in achieving security for much more than 1/3 corruptions. To that end, we give two compilers for MPC protocols, which assume a simple public-key infrastructure, and achieve semi-honest security for all-but-one corruptions. Our first compiler assumes hardness of the learning-with-errors (LWE) problem, and works for any MPC protocol with ``short\u27\u27 output---that is, where the output of the protocol can fit into the storage space of one machine, for instance protocols that output a trained machine learning model. Our second compiler works for any MPC protocol (even ones with a long output, such as sorting) but assumes, in addition to LWE, indistinguishability obfuscation and a circular secure variant of threshold FHE. Both protocols allow the attacker to choose corrupted parties based on the trusted setup, an improvement over Chan et al., whose protocol requires that the CRS is chosen independently of the attacker\u27s choices
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