Results 11 to 20 of about 3,214 (260)
Privacy-preserving machine learning based on secure two-party computations
Безопасность информационных технологий, 2021 The paper is devoted to the analysis of privacy-preserving machine learning systems based on secure two-party computations. The paper provides introductory information about privacy-preserving machine learning systems, analyses the goals and objectives ...
Sergey V. Zapechnikov +1 more
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Cloud-Assisted Private Set Intersection via Multi-Key Fully Homomorphic Encryption
Mathematics, 2023 With the development of cloud computing and big data, secure multi-party computation, which can collaborate with multiple parties to deal with a large number of transactions, plays an important role in protecting privacy.
Cunqun Fan +6 more
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HACCLE: metaprogramming for secure multi-party computation [PDF]
Proceedings of the 20th ACM SIGPLAN International Conference on Generative Programming: Concepts and Experiences, 2021 Cryptographic techniques have the potential to enable distrusting parties to collaborate in fundamentally new ways, but their practical implementation poses numerous challenges. An important class of such cryptographic techniques is known as Secure Multi-Party Computation (MPC).
Yuyan Bao +19 more
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Secure Multi-Party Computation
, 2023 AbstractSecure multi-party computation enables a group of parties to compute a function while jointly keeping their private inputs secret. The term “secure” indicates the latter property where the private inputs used for computation are kept secret from all other parties.
Merino, Louis Henri +1 more
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Privacy-Preserving Determination of Secret Interval and Threshold
Jisuanji kexue yu tansuo, 2020 Secure multi-party computation (SMC) is a research hotspot in cryptography in recent years, and is also a key technology for information security protection.
CHENG Wen, LI Shundong, WANG Wenli
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Efficient Secure Multi-party Computation [PDF]
, 2000 Since the introduction of secure multi-party computation, all proposed protocols that provide security against cheating players suffer from very high communication complexities. The most efficient unconditionally secure protocols among n players, tolerating cheating by up to t < n/3 of them, require communicating O(n6) field elements for each ...
Martin Hirt +2 more
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Secure multi-party computation in large networks [PDF]
Distributed Computing, 2016 We describe scalable protocols for solving the secure multi-party computation (MPC) problem among a large number of parties. We consider both the synchronous and the asynchronous communication models. In the synchronous setting, our protocol is secure against a static malicious adversary corrupting less than a $1/3$ fraction of the parties.
Varsha Dani +4 more
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Privacy-Aware MapReduce Based Multi-Party Secure Skyline Computation
Information, 2019 Selecting representative objects from a large-scale dataset is an important task for understanding the dataset. Skyline is a popular technique for selecting representative objects from a large dataset.
Saleh Ahmed +6 more
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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 +4 more
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A Privacy-preserving Spatial Outlier Detection Method [PDF]
Jisuanji gongcheng, 2017 Foucusing on the issue that the existing spatial outlier detection methods fail to effectively solve the problem of guaranteeing both the data security and the validity of detection results at the same time,a privacy-preserving spatial outlier detection ...
YU Qingying,LUO Yonglong,CHEN Fulong,ZHENG Xiaoyao
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