Zobrazeno 1 - 10
of 98
pro vyhledávání: '"Changgen Peng"'
Publikováno v:
Mathematical Biosciences and Engineering, Vol 20, Iss 12, Pp 21315-21336 (2023)
In many fields, such as medicine and the computer industry, databases are vital in the process of information sharing. However, databases face the risk of being stolen or misused, leading to security threats such as copyright disputes and privacy bre
Externí odkaz:
https://doaj.org/article/1a59cada61474639a9a825425d068215
Publikováno v:
Journal of King Saud University: Computer and Information Sciences, Vol 35, Iss 10, Pp 101854- (2023)
With the increasing concern for public privacy protection, Secret Image Sharing (SIS) has garnered significant attention among researchers. The goal of SIS is to split a secret image into multiple shadows, rendering it unrecoverable unless a specific
Externí odkaz:
https://doaj.org/article/ad7cbb312ff4499e8c56b58a6420de2e
Publikováno v:
Axioms, Vol 13, Iss 4, p 254 (2024)
The distributed training of federated machine learning, referred to as federated learning (FL), is discussed in models by multiple participants using local data without compromising data privacy and violating laws. In this paper, we consider the trai
Externí odkaz:
https://doaj.org/article/9cbaf745b8474a3599ab7bc171aae1ca
Publikováno v:
Entropy, Vol 26, Iss 2, p 164 (2024)
Federated learning (FL) is a distributed machine learning framework that enables scattered participants to collaboratively train machine learning models without revealing information to other participants. Due to its distributed nature, FL is suscept
Externí odkaz:
https://doaj.org/article/904a7897c5644e0c986dfedf857742c1
Publikováno v:
Entropy, Vol 25, Iss 12, p 1607 (2023)
Deep learning is one of the most exciting and promising techniques in the field of artificial intelligence (AI), which drives AI applications to be more intelligent and comprehensive. However, existing deep learning techniques usually require a large
Externí odkaz:
https://doaj.org/article/8140a7e1a3174f0594807e623575f293
Publikováno v:
Entropy, Vol 25, Iss 9, p 1334 (2023)
Blockchain integrates peer-to-peer networks, distributed consensus, smart contracts, cryptography, etc. It has the unique advantages of weak centralization, anti-tampering, traceability, openness, transparency, etc., and is widely used in various fie
Externí odkaz:
https://doaj.org/article/4613bc39507d41b889d141f26aa296ad
Publikováno v:
Tongxin xuebao, Vol 43, Pp 149-160 (2022)
Aiming at the problem of restricted access failure in current black box membership inference attacks, a PCA-based membership inference attack was proposed.Firstly, in order to solve the restricted access problem of black box membership inference atta
Externí odkaz:
https://doaj.org/article/672b3a4912814fec97244d0d646adb6d
Publikováno v:
Axioms, Vol 12, Iss 7, p 636 (2023)
Federated learning (FL) is a distributed machine learning framework that can effectively help multiple players to use data to train federated models while complying with their privacy, data security, and government regulations. Due to federated model
Externí odkaz:
https://doaj.org/article/2c14e857982a41dabc7d7e02126b151d
Publikováno v:
Tongxin xuebao, Vol 42, Pp 75-86 (2021)
To solve the dynamic update of access rights in attribute-based collaborative access control, a novel scheme was proposed with the revocation of attribute, user and collaborative policy.A formal definition and a security model were presented, the gro
Externí odkaz:
https://doaj.org/article/b91659108afa401184929cab35ffda35
Publikováno v:
Tongxin xuebao, Vol 42, Pp 139-149 (2021)
Due to the advantages of cloud computing, such as virtualization and high scalability, individuals and enterprises are willing to outsource local data storage and computing to cloud servers.However, encryption breaks the linkability between the data.
Externí odkaz:
https://doaj.org/article/28c64414c0604f5a8b37b19d5887edb3