Results 21 to 30 of about 938 (179)

Quantum privacy‐preserving service for secure lane change in vehicular networks

IET Quantum Communication, 2023
Secure Multiparty Computation (SMC) enables multiple parties to cooperate securely without compromising their privacy. SMC has the potential to offer solutions for privacy obstacles in vehicular networks.
Zeinab Rahmani, Luis S. Barbosa, Armando N. Pinto   +2 more
doaj   +1 more source

Robust peer-to-peer learning via secure multi-party computation

Journal of Information and Intelligence, 2023
To solve the data island problem, federated learning (FL) provides a solution paradigm where each client sends the model parameters but not the data to a server for model aggregation.
Yongkang Luo, Wenjian Luo, Ruizhuo Zhang, Hongwei Zhang, Yuhui Shi   +4 more
doaj   +1 more source

Generalized Secure and Dynamic Decentralized Reputation System With a Dishonest Majority

IEEE Access, 2023
Reputation management systems are essential for establishing trust among network users. They are tools for reinforcing cooperation and sanctioning malicious behavior.
Khalid Mrabet, Faissal El Bouanani, Hussain Ben-Azza   +2 more
doaj   +1 more source

Secure Multiparty Computation for Privacy-Preserving Data Mining

The Journal of Privacy and Confidentiality, 2009
In this paper, we survey the basic paradigms and notions of secure multiparty computation and discuss their relevance to the field of privacy-preserving data mining. In addition to reviewing definitions and constructions for secure multiparty computation,
Yehuda Lindell, Benny Pinkas
doaj   +1 more source

Fair and Secure Multi-Party Computation with Cheater Detection

Cryptography, 2021
Secure multi-party computation (SMC) is a cryptographic protocol that allows participants to compute the desired output without revealing their inputs. A variety of results related to increasing the efficiency of SMC protocol have been reported, and thus,
Minhye Seo
doaj   +1 more source

Secure multiparty computations without computers

Theoretical Computer Science, 1998
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Valtteri Niemi, Ari Renvall
openaire   +2 more sources

Secure Multiparty Computation Goes Live [PDF]

, 2009
In this note, we report on the first large-scale and practical application of secure multiparty computation, which took place in January 2008. We also report on the novel cryptographic protocols that were used. This work was supported by the Danish Strategic Research Council and the European Commision.
Bøgetoft, Peter, Lund Christensen, Dan, Damgård, Ivan Bjerre, Geisler, Martin, Jacobsen, Thomas, Krøigaard, Mikkel, Nielsen, Janus Dam, Nielsen, Jesper Buus, Nielsen, Kurt, Pagter, Jakob Illeborg, Schwartzbach, Michael Ignatieff, Toft, Tomas, Nielsen, Kurt   +12 more
openaire   +7 more sources

Two-Cloud-Servers-Assisted Secure Outsourcing Multiparty Computation

The Scientific World Journal, 2014
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.
Yi Sun, Qiaoyan Wen, Yudong Zhang, Hua Zhang, Zhengping Jin, Wenmin Li   +5 more
doaj   +1 more source

AntNest: Fully Non-Interactive Secure Multi-Party Computation

IEEE Access, 2018
In this paper, we focus on the research of non-interactive secure multi-party computation. At first, we propose a fully homomorphic non-interactive verifiable secret sharing (FHNVSS) scheme.
Lijing Zhou, Licheng Wang, Yiru Sun, Tianyi Ai   +3 more
doaj   +1 more source

A Quantum Protocol for Secure Manhattan Distance Computation

IEEE Access, 2020
Secure Manhattan distance computation allows two parties to privately compute the Manhattan distance of their points, which is important and has broad applications.
Wen Liu, Wei Zhang
doaj   +1 more source