Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Renwan BI"'
Publikováno v:
Digital Communications and Networks, Vol 10, Iss 2, Pp 380-388 (2024)
With the maturity and development of 5G field, Mobile Edge CrowdSensing (MECS), as an intelligent data collection paradigm, provides a broad prospect for various applications in IoT. However, sensing users as data uploaders lack a balance between dat
Externí odkaz:
https://doaj.org/article/4b2e5cc7373244f8aecd8ec3820fdc6a
Publikováno v:
网络与信息安全学报, Vol 8, Pp 139-150 (2022)
In response to the existing problems that the federated learning might lead to the reduction of aggregation efficiency by handing the majority of irregular users and the leak of parameter privacy by adopting plaintext communication, a framework of pr
Externí odkaz:
https://doaj.org/article/3fcb571d3433400db6bbaa4f94bc966d
Publikováno v:
Tongxin xuebao, Vol 43, Pp 127-137 (2022)
Aiming at the problems of data leakage of perceptual image and computational inefficiency of privacy-preserving classification framework in edge-side computing environment, a lightweight and privacy-preserving classification framework (PPCF) was prop
Externí odkaz:
https://doaj.org/article/e41b7715179448649a7ea4717db54650
Publikováno v:
Tongxin xuebao, Vol 41, Pp 188-201 (2020)
Aiming at the problem of image privacy leakage and computing efficiency in edge environment,a lightweight and secure region proposal network (SecRPN) was proposed.A series of secure computing protocols were designed based on the additive secret shari
Externí odkaz:
https://doaj.org/article/fa766de8df294b8f8cd69c2b5c5fa5f8
Publikováno v:
网络与信息安全学报, Vol 6, Pp 130-139 (2020)
Aiming at the information leakage problem in the process of deep neural network model calculation,a series of secure and efficient interactive computing protocols were designed between two non-collusive edge servers in combination with the additive s
Externí odkaz:
https://doaj.org/article/1aa39e70518e4ee2b57e298bf999f9ab
Publikováno v:
网络与信息安全学报, Vol 5, Pp 75-84 (2019)
In mobile crowd sensing(MCS),attackers can reconstruct the social circle among sensing users,who use the social association information among sensing users and the correlation between the sensing user’s identity and sensing data to further attack a
Externí odkaz:
https://doaj.org/article/409ffdd59d5748d4ac512dc7d7555b70
Publikováno v:
IEEE Internet of Things Journal. 10:2314-2329
Publikováno v:
IEEE/ACM Transactions on Computational Biology and Bioinformatics. :1-12
Publikováno v:
IEEE Transactions on Intelligent Transportation Systems. 23:24979-24990
Publikováno v:
IEEE Internet of Things Journal. 9:2787-2801
Collaborative perception enables autonomous vehicles to exchange sensor data among each other to achieve cooperative object classification, which is considered an effective means to improve the perception accuracy of connected autonomous vehicles (CA