1,475 research outputs found

    Practical Homomorphic Encryption Over the Integers for Secure Computation in the Cloud

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    We present novel homomorphic encryption schemes for integer arithmetic, intended primarily for use in secure single-party computation in the cloud. These schemes are capable of securely computing arbitrary degree polynomials homomorphically. In practice, ciphertext size and running times limit the polynomial degree, but this appears sufficient for most practical applications. We present four schemes, with increasing levels of security, but increasing computational overhead. Two of the schemes provide strong security for high-entropy data. The remaining two schemes provide strong security regardless of this assumption. These four algorithms form the first two levels of a hierarchy of schemes which require linearly decreasing entropy. We have evaluated these four algorithms by computing low-degree polynomials. The timings of these computations are extremely favourable by comparison with even the best of existing methods, and dramatically out-perform running times of directly comparable schemes by a factor of up to 1000, and considerably more than that for fully homomorphic schemes, used in the same context. The results clearly demonstrate the practical applicability of our schemes

    Practical homomorphic encryption over the integers for secure computation in the cloud

    Get PDF
    We present novel homomorphic encryption schemes for integer arithmetic, intended primarily for use in secure single-party computation in the cloud. These schemes are capable of securely computing arbitrary degree polynomials homomorphically. In practice, ciphertext size and running times limit the polynomial degree, but this appears sufficient for most practical applications. We present four schemes, with increasing levels of security, but increasing computational overhead. Two of the schemes provide strong security for high-entropy data. The remaining two schemes provide strong security regardless of this assumption. These four algorithms form the first two levels of a hierarchy of schemes, and we also present the general cases of each scheme. We further elaborate how a fully homomorphic system can be constructed from one of our general cases. In addition, we present a variant based upon Chinese Remainder Theorem secret sharing. We detail extensive evaluation of the first four algorithms of our hierarchy by computing low-degree polynomials. The timings of these computations are extremely favourable by comparison with even the best of existing methods and dramatically outperform many well-publicised schemes. The results clearly demonstrate the practical applicability of our schemes

    Faster Secure Arithmetic Computation Using Switchable Homomorphic Encryption

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    Secure computation on encrypted data stored on untrusted clouds is an important goal. Existing secure arithmetic computation techniques, such as fully homomorphic encryption (FHE) and somewhat homomorphic encryption (SWH), have prohibitive performance and/or storage costs for the majority of practical applications. In this work, we investigate a new secure arithmetic computation primitive called switchable homomorphic encryption (SHE) that securely switches between existing inexpensive partially homomorphic encryption techniques to evaluate arbitrary arithmetic circuits over integers. SHE is suited for use in a two-cloud model that is practical, but which makes stronger assumptions than the standard single-cloud server model. The security of our SHE solution relies on two non-colluding parties, in which security holds as long as one of them is honest. We benchmark SHE directly against existing secure arithmetic computation techniques---FHE and SWH---on real clouds (Amazon and Rackspace) using microbenchmarks involving fundamental operations utilized in many privacy-preserving computation applications. Experimentally, we find that SHE offers a new design point for computing on large data---it has reasonable ciphertext and key sizes, and is consistently faster by several (2--3) orders of magnitude compared to FHE and SWH on circuits involving long chain of multiplications. SHE exhibits slower performance only in certain cases, when batch (or parallel) homomorphic evaluation is possible, only against SWH schemes (which have limited expressiveness and potentially high ciphertext and key storage costs)

    A Survey on Homomorphic Encryption Schemes: Theory and Implementation

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    Legacy encryption systems depend on sharing a key (public or private) among the peers involved in exchanging an encrypted message. However, this approach poses privacy concerns. Especially with popular cloud services, the control over the privacy of the sensitive data is lost. Even when the keys are not shared, the encrypted material is shared with a third party that does not necessarily need to access the content. Moreover, untrusted servers, providers, and cloud operators can keep identifying elements of users long after users end the relationship with the services. Indeed, Homomorphic Encryption (HE), a special kind of encryption scheme, can address these concerns as it allows any third party to operate on the encrypted data without decrypting it in advance. Although this extremely useful feature of the HE scheme has been known for over 30 years, the first plausible and achievable Fully Homomorphic Encryption (FHE) scheme, which allows any computable function to perform on the encrypted data, was introduced by Craig Gentry in 2009. Even though this was a major achievement, different implementations so far demonstrated that FHE still needs to be improved significantly to be practical on every platform. First, we present the basics of HE and the details of the well-known Partially Homomorphic Encryption (PHE) and Somewhat Homomorphic Encryption (SWHE), which are important pillars of achieving FHE. Then, the main FHE families, which have become the base for the other follow-up FHE schemes are presented. Furthermore, the implementations and recent improvements in Gentry-type FHE schemes are also surveyed. Finally, further research directions are discussed. This survey is intended to give a clear knowledge and foundation to researchers and practitioners interested in knowing, applying, as well as extending the state of the art HE, PHE, SWHE, and FHE systems.Comment: - Updated. (October 6, 2017) - This paper is an early draft of the survey that is being submitted to ACM CSUR and has been uploaded to arXiv for feedback from stakeholder

    A Verifiable Fully Homomorphic Encryption Scheme for Cloud Computing Security

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    Performing smart computations in a context of cloud computing and big data is highly appreciated today. Fully homomorphic encryption (FHE) is a smart category of encryption schemes that allows working with the data in its encrypted form. It permits us to preserve confidentiality of our sensible data and to benefit from cloud computing powers. Currently, it has been demonstrated by many existing schemes that the theory is feasible but the efficiency needs to be dramatically improved in order to make it usable for real applications. One subtle difficulty is how to efficiently handle the noise. This paper aims to introduce an efficient and verifiable FHE based on a new mathematic structure that is noise free
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