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Author:

Cai, Fangbo (Cai, Fangbo.) | He, Jingsha (He, Jingsha.) (Scholars:何泾沙) | Mu, Pengyu (Mu, Pengyu.) | Han, Song (Han, Song.) | Hou, Ziqiang (Hou, Ziqiang.) | Zhu, Nafei (Zhu, Nafei.)

Indexed by:

EI Scopus

Abstract:

Classification and regression prediction of access objects in distributed access control model is a very important basic task in distributed access control model. Machine learning plays an important role in the field of intelligent access control in the future, especially in the application of machine learning methods to solve classification and regression problems. The paper proposes a learning method of distributed collaborative training, which can reduce the communication consumption of node policy update and increase the access execution margin of a single node. Improve model performance. © 2020, Springer Nature Singapore Pte Ltd.

Keyword:

Computation theory Machine learning Access control Networks (circuits)

Author Community:

  • [ 1 ] [Cai, Fangbo]Faculty of Information Technology, Beijing University of Technology, Beijing, China
  • [ 2 ] [He, Jingsha]Faculty of Information Technology, Beijing University of Technology, Beijing, China
  • [ 3 ] [Mu, Pengyu]Faculty of Information Technology, Beijing University of Technology, Beijing, China
  • [ 4 ] [Han, Song]Faculty of Information Technology, Beijing University of Technology, Beijing, China
  • [ 5 ] [Hou, Ziqiang]Faculty of Information Technology, Beijing University of Technology, Beijing, China
  • [ 6 ] [Zhu, Nafei]Faculty of Information Technology, Beijing University of Technology, Beijing, China

Reprint Author's Address:

  • [cai, fangbo]faculty of information technology, beijing university of technology, beijing, china

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Source :

ISSN: 1876-1100

Year: 2020

Volume: 551 LNEE

Page: 904-912

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 9

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