scholarly journals An Efficient HPRA-Based Multiclient Verifiable Computation: Transform and Instantiation

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Shuaijianni Xu
Keyword(s):  
Homomorphic Encryption ◽  
Fully Homomorphic Encryption ◽  
Linear Combinations ◽  
Verifiable Computation ◽  
Garbled Circuits

Choi, Katz, Kumaresan, and Cid put forward the conception of multiclient noninteractive verifiable computation (MVC), enabling a group of clients to outsource computation of a function of f . CKKC’s MVC is impractical due to their dependence on fully homomorphic encryption (FHE) and garbled circuits (GCs). In this paper, with the goal of satisfying practical requirements, a general transform is presented from the homomorphic proxy re-authenticator (HPRA) of Deler, Ramacher, and Slamanig to MVC schemes. MVC constructions in this particular study tend to be more efficient once the underlying HPRA avoids introducing FHE and GCs. By deploying the transform to DRS’s HPRA scheme, a specific MVC scheme for calculating the linear combinations of vectors has been proposed. It can be understood that it is the first feasible and implementable MVC scheme so far, and the instantiation solution has a great advantage in efficiency compared with related works.

scholarly journals A Verifiable Fully Homomorphic Encryption Scheme for Cloud Computing Security

Technologies ◽  
2019 ◽  
Vol 7 (1) ◽  
pp. 21
Author(s):  
Ahmed EL-YAHYAOUI ◽  
Mohamed Dafir ECH-CHERIF EL KETTANI
Keyword(s):  
Cloud Computing ◽  
Homomorphic Encryption ◽  
Encryption Scheme ◽  
Fully Homomorphic Encryption ◽  
Sensitive Data ◽  
Verifiable Computation ◽  
Multiplication Operation ◽  
Matrix Operations ◽  
Encryption Schemes ◽  
Simple Matrix

Performing smart computations in a context of cloud computing and big data is highly appreciated today. It allows customers to fully benefit from cloud computing capacities (such as processing or storage) without losing confidentiality of sensitive data. Fully homomorphic encryption (FHE) is a smart category of encryption schemes that enables working with the data in its encrypted form. It permits us to preserve confidentiality of our sensible data and to benefit from cloud computing capabilities. While FHE is combined with verifiable computation, it offers efficient procedures for outsourcing computations over encrypted data to a remote, but non-trusted, cloud server. The resulting scheme is called Verifiable Fully Homomorphic Encryption (VFHE). 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 symmetric verifiable FHE based on a new mathematic structure that is noise free. In our encryption scheme, the noise is constant and does not depend on homomorphic evaluation of ciphertexts. The homomorphy of our scheme is obtained from simple matrix operations (addition and multiplication). The running time of the multiplication operation of our encryption scheme in a cloud environment has an order of a few milliseconds.

scholarly journals Privacy-preserving verifiable delegation of polynomial and matrix functions

2020 ◽  
Vol 14 (1) ◽  
pp. 153-171
Author(s):  
Liang Feng Zhang ◽  
Reihaneh Safavi-Naini
Keyword(s):  
High Efficiency ◽  
Homomorphic Encryption ◽  
Real Life ◽  
Security Requirements ◽  
Security Model ◽  
Boolean Circuit ◽  
Curve Reconstruction ◽  
Verifiable Computation ◽  
Matrix Vector Multiplication ◽  
Garbled Circuits

AbstractOutsourcing computation has gained significant popularity in recent years due to the development of cloud computing and mobile services. In a basic outsourcing model, a client delegates computation of a function f on an input x to a server. There are two main security requirements in this setting: guaranteeing the server performs the computation correctly, and protecting the client’s input (and hence the function value) from the server. The verifiable computation model of Gennaro, Gentry and Parno achieves the above requirements, but the resulting schemes lack efficiency. This is due to the use of computationally expensive primitives such as fully homomorphic encryption (FHE) and garbled circuits, and the need to represent f as a Boolean circuit. Also, the security model does not allow verification queries, which implies the server cannot learn if the client accepts the computation result. This is a weak security model that does not match many real life scenarios. In this paper, we construct efficient (i.e., without using FHE, garbled circuits and Boolean circuit representations) verifiable computation schemes that provide privacy for the client’s input, and prove their security in a strong model that allows verification queries. We first propose a transformation that provides input privacy for a number of existing schemes for verifiable delegation of multivariate polynomial f over a finite field. Our transformation is based on noisy encoding of x and keeps x semantically secure under the noisy curve reconstruction (CR) assumption. We then propose a construction for verifiable delegation of matrix-vector multiplication, where the delegated function f is a matrix and the input to the function is a vector. The scheme uses PRFs with amortized closed-form efficiency and achieves high efficiency. We outline applications of our results to outsourced two-party protocols.

A Neural Network Application of Fully Homomorphic Encryption for Cloud Computing

2020 ◽  
Author(s):  
Megha Kolhekar ◽  
Ashish Pandey ◽  
Ayushi Raina ◽  
Rijin Thomas ◽  
Vaibhav Tiwari ◽  
...  
Keyword(s):  
Neural Network ◽  
Cloud Computing ◽  
Homomorphic Encryption ◽  
Fully Homomorphic Encryption ◽  
Network Application

A fully homomorphic encryption based on magic number fragmentation and El‐Gamal encryption: Smart healthcare use case

2021 ◽  
Author(s):  
Mostefa Kara ◽  
Abdelkader Laouid ◽  
Mohammed Amine Yagoub ◽  
Reinhardt Euler ◽  
Saci Medileh ◽  
...  
Keyword(s):  
Homomorphic Encryption ◽  
Magic Number ◽  
Use Case ◽  
Healthcare Use ◽  
Fully Homomorphic Encryption ◽  
Smart Healthcare

scholarly journals A Password Meter without Password Exposure

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 345
Author(s):  
Pyung Kim ◽  
Younho Lee ◽  
Youn-Sik Hong ◽  
Taekyoung Kwon
Keyword(s):  
Performance Enhancement ◽  
Homomorphic Encryption ◽  
Optimization Techniques ◽  
Third Party ◽  
Fully Homomorphic Encryption ◽  
Performance Achievement ◽  
Server Side ◽  
On Line ◽  
Internal Mechanism ◽  
High Chance

To meet password selection criteria of a server, a user occasionally needs to provide multiple choices of password candidates to an on-line password meter, but such user-chosen candidates tend to be derived from the user’s previous passwords—the meter may have a high chance to acquire information about a user’s passwords employed for various purposes. A third party password metering service may worsen this threat. In this paper, we first explore a new on-line password meter concept that does not necessitate the exposure of user’s passwords for evaluating user-chosen password candidates in the server side. Our basic idea is straightforward; to adapt fully homomorphic encryption (FHE) schemes to build such a system but its performance achievement is greatly challenging. Optimization techniques are necessary for performance achievement in practice. We employ various performance enhancement techniques and implement the NIST (National Institute of Standards and Technology) metering method as seminal work in this field. Our experiment results demonstrate that the running time of the proposed meter is around 60 s in a conventional desktop server, expecting better performance in high-end hardware, with an FHE scheme in HElib library where parameters support at least 80-bit security. We believe the proposed method can be further explored and used for a password metering in case that password secrecy is very important—the user’s password candidates should not be exposed to the meter and also an internal mechanism of password metering should not be disclosed to users and any other third parties.

scholarly journals Accelerating Fully Homomorphic Encryption Through Architecture-centric Analysis and Optimization

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Wonkyung Jung ◽  
Eojin Lee ◽  
Sangpyo Kim ◽  
Jongmin Kim ◽  
Namhoon Kim ◽  
...  
Keyword(s):  
Homomorphic Encryption ◽  
Fully Homomorphic Encryption
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