1,826 research outputs found
Privacy preserving distributed optimization using homomorphic encryption
This paper studies how a system operator and a set of agents securely execute
a distributed projected gradient-based algorithm. In particular, each
participant holds a set of problem coefficients and/or states whose values are
private to the data owner. The concerned problem raises two questions: how to
securely compute given functions; and which functions should be computed in the
first place. For the first question, by using the techniques of homomorphic
encryption, we propose novel algorithms which can achieve secure multiparty
computation with perfect correctness. For the second question, we identify a
class of functions which can be securely computed. The correctness and
computational efficiency of the proposed algorithms are verified by two case
studies of power systems, one on a demand response problem and the other on an
optimal power flow problem.Comment: 24 pages, 5 figures, journa
A Survey on Homomorphic Encryption Schemes: Theory and Implementation
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 First Practical Fully Homomorphic Crypto-Processor Design: The Secret Computer is Nearly Here
Following a sequence of hardware designs for a fully homomorphic
crypto-processor - a general purpose processor that natively runs encrypted
machine code on encrypted data in registers and memory, resulting in encrypted
machine states - proposed by the authors in 2014, we discuss a working
prototype of the first of those, a so-called `pseudo-homomorphic' design. This
processor is in principle safe against physical or software-based attacks by
the owner/operator of the processor on user processes running in it. The
processor is intended as a more secure option for those emerging computing
paradigms that require trust to be placed in computations carried out in remote
locations or overseen by untrusted operators.
The prototype has a single-pipeline superscalar architecture that runs
OpenRISC standard machine code in two distinct modes. The processor runs in the
encrypted mode (the unprivileged, `user' mode, with a long pipeline) at 60-70%
of the speed in the unencrypted mode (the privileged, `supervisor' mode, with a
short pipeline), emitting a completed encrypted instruction every 1.67-1.8
cycles on average in real trials.Comment: 6 pages, draf
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