Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

International journal of network security

A Secure and Efficient Computation Outsourcing Scheme for Multi-Users.

Vemuri Sudarsan Rao, N. Satyanarayana

Published Jan 1, 2019• 0 citations
OpenAlex

Abstract

The outsourcing process is computationally secure if it is performed without unveiling to the other external agent or cloud, either the original data or the actual solution to the computations. Secure multiparty computation computes a certain function without revealing their private secret information.

Related papers

Two-Cloud-Servers-Assisted Secure Outsourcing Multiparty Computation

Yi Sun, Qiaoyan Wen, Yudong Zhang +3 more

We focus on how to securely outsource computation task to the cloud and propose a secure outsourcing multiparty computation protocol on lattice-based encrypted data in two-cloud-servers scenario. Our main idea is to transform the outsourced data respectively encrypted by different users' public keys to the ones that are encrypted by the same two private keys of the two assisted servers so that it is feasible to operate on the transformed ciphertexts to compute an encrypted result following the function to be computed. In order to keep the privacy of the result, the two servers cooperatively produce a custom-made result for each user that is authorized to get the result so that all authorized users can recover the desired result while other unauthorized ones including the two servers cannot. Compared with previous research, our protocol is completely noninteractive between any users, and both of the computation and the communication complexities of each user in our solution are independent of the computing function.

The Scientific World JOURNAL•Jan 1, 2014•8 citations

A Non-interactive Secure Outsourced Computation Scheme in Multi-party Cloud

Shu Guo, Haixia Xu

Cloud computing is becoming concerned both in academia and industry and one of the most important applications is outsourced computation. A computationally weak client out sources tasks to one or more workers in cloud, and this is called outsourced computation. This paper presents an outsourced protocol based on Kamara's scheme [19], and it allows the client to outsource their computation to more than one workers while keeping privacy and correctness. Kamara proposed security definitions, while regretfully, didn't show the description of the protocol. This paper presents a specific scheme in which the workers computes directly on shares that client send to them, so the workers don't have to interactive with each other. This protocol has these advantages: the protocol keeps privacy of the original input, the workers have no interactivity with each other during the execution, the protocol keeps the threshold unchanged.

International Conference on Intelligent Networking and Collaborative Systems (INCoS)•Sep 1, 2012•2 citations

Secure Computation on Additive Shares.

Zhihua Xia, Qi Gu, Wenhao Zhou +2 more

The rapid development of cloud computing has probably benefited each of us. However, the privacy risks brought by untrusty cloud servers arise the attention of more and more people and legislatures. In the last two decades, plenty of works seek the way of outsourcing various specific tasks while ensuring the security of private data. Although the addition and multiplication are enough for implementing any functions, the direct utilization of existing schemes like homomorphic encryption will lead to significant efficiency and accuracy loss, which is not suitable for outsourcing computation tasks. The tasks to be outsourced are endless, however, the involved calculations are similar. In this paper, inspired by additive secret sharing and multiplicative secret sharing technologies, we construct a series of novel protocols which support the common secure calculations on numbers (e.g., basic elementary functions) or matrices (e.g., solve eigenvectors) in arbitrary $n$ number of servers ($n \geq 2$), and the $n$-party protocols ensure the security of the original data even if $n-1$ servers collude. All protocols we designed only need constant interaction rounds, and we demonstrate them under universally composability security. We believe that these protocols can provide a new basic tool for actual outsourced tasks.

•Sep 28, 2020•0 citations

A Secure and Efficient Computation Outsourcing Scheme for Multi-users

Vemuri Sudarsan Rao, N. Satyanarayana

Communications in computer and information science•Jan 1, 2018•1 citation

Efficiently Outsourcing Multiparty Computation under Multiple Keys.

Peter Andreas, Erik Tews, Stefan Katzenbeisser

Abstract. Secure Multiparty Computation (SMC) enables a set of users to evaluate certain functionalities on their respective inputs while keeping these inputs encrypted throughout the computation. Inmanyscenarios, however, outsourcingthesecomputations toanuntrustedserver is desirable, sothattheservercanperform thecomputationonbehalfoftheusers.Unfortunately, existing solutions are either inefficient, rely heavily on user interaction, or require the inputs to be encrypted under the same key—drawbacks making the employment in practice very limited. We propose the first general-purpose construction that avoids all these drawbacks: it is efficient, it requires no user interaction whatsoever (except for data up- and download), and it allows evaluating any dynamically chosen function on inputs encrypted under different independent public keys. Our solution assumes the existence of two non-colluding but untrusted servers that jointly perform the computation by means of a cryptographic protocol. This protocol is provably secure in the semi-honest model. We demonstrate the applicability of our result in two real-world scenarios from different domains: Privacy-Preserving Face Recognition and Private Smart Metering. Finally, we give a performance analysis of our general-purpose construction to highlight its practicability.

•Jan 1, 2013•2 citations

Secure Multi-Party Computation with a Helper

Johannes Schneider

A client wishes to outsource computation on confidential data to a network of parties. He does not trust a single party but believes that multiple parties do not collude. To solve this problem, we use the idea of treating one of the parties as a helper. A helper assists computation only. Often using more parties ensures confidentiality despite more corrupted parties. This does not hold for adding a helper. But a helper can in some cases lower the amount of communication asymptotically to the theoretical minimum of one bit per AND gate, improving significantly on schemes without a helper. It can also allow for very efficient computations of certain functions, as we show for the exponential function with public base.

arXiv:1508.07690•Aug 31, 2015•2 citations
We focus on how to securely outsource computation task to the cloud and propose a secure outsourcing multiparty computation protocol on lattice-based encrypted data in two-cloud-servers scenario. Our main idea is to transform the outsourced data respectively encrypted by different users' public keys to the ones that are encrypted by the same two private keys of the two assisted servers so that it is feasible to operate on the transformed ciphertexts to compute an encrypted result following the function to be computed. In order to keep the privacy of the result, the two servers cooperatively produce a custom-made result for each user that is authorized to get the result so that all authorized users can recover the desired result while other unauthorized ones including the two servers cannot. Compared with previous research, our protocol is completely noninteractive between any users, and both of the computation and the communication complexities of each user in our solution are independent of the computing function.
Cloud computing is becoming concerned both in academia and industry and one of the most important applications is outsourced computation. A computationally weak client out sources tasks to one or more workers in cloud, and this is called outsourced computation. This paper presents an outsourced protocol based on Kamara's scheme [19], and it allows the client to outsource their computation to more than one workers while keeping privacy and correctness. Kamara proposed security definitions, while regretfully, didn't show the description of the protocol. This paper presents a specific scheme in which the workers computes directly on shares that client send to them, so the workers don't have to interactive with each other. This protocol has these advantages: the protocol keeps privacy of the original input, the workers have no interactivity with each other during the execution, the protocol keeps the threshold unchanged.
The rapid development of cloud computing has probably benefited each of us. However, the privacy risks brought by untrusty cloud servers arise the attention of more and more people and legislatures. In the last two decades, plenty of works seek the way of outsourcing various specific tasks while ensuring the security of private data. Although the addition and multiplication are enough for implementing any functions, the direct utilization of existing schemes like homomorphic encryption will lead to significant efficiency and accuracy loss, which is not suitable for outsourcing computation tasks. The tasks to be outsourced are endless, however, the involved calculations are similar. In this paper, inspired by additive secret sharing and multiplicative secret sharing technologies, we construct a series of novel protocols which support the common secure calculations on numbers (e.g., basic elementary functions) or matrices (e.g., solve eigenvectors) in arbitrary nnn number of servers (n≥2n \geq 2n≥2), and the nnn-party protocols ensure the security of the original data even if n−1n-1n−1 servers collude. All protocols we designed only need constant interaction rounds, and we demonstrate them under universally composability security. We believe that these protocols can provide a new basic tool for actual outsourced tasks.
Abstract. Secure Multiparty Computation (SMC) enables a set of users to evaluate certain functionalities on their respective inputs while keeping these inputs encrypted throughout the computation. Inmanyscenarios, however, outsourcingthesecomputations toanuntrustedserver is desirable, sothattheservercanperform thecomputationonbehalfoftheusers.Unfortunately, existing solutions are either inefficient, rely heavily on user interaction, or require the inputs to be encrypted under the same key—drawbacks making the employment in practice very limited. We propose the first general-purpose construction that avoids all these drawbacks: it is efficient, it requires no user interaction whatsoever (except for data up- and download), and it allows evaluating any dynamically chosen function on inputs encrypted under different independent public keys. Our solution assumes the existence of two non-colluding but untrusted servers that jointly perform the computation by means of a cryptographic protocol. This protocol is provably secure in the semi-honest model. We demonstrate the applicability of our result in two real-world scenarios from different domains: Privacy-Preserving Face Recognition and Private Smart Metering. Finally, we give a performance analysis of our general-purpose construction to highlight its practicability.
A client wishes to outsource computation on confidential data to a network of parties. He does not trust a single party but believes that multiple parties do not collude. To solve this problem, we use the idea of treating one of the parties as a helper. A helper assists computation only. Often using more parties ensures confidentiality despite more corrupted parties. This does not hold for adding a helper. But a helper can in some cases lower the amount of communication asymptotically to the theoretical minimum of one bit per AND gate, improving significantly on schemes without a helper. It can also allow for very efficient computations of certain functions, as we show for the exponential function with public base.