PMID- 32245041
OWN - NLM
STAT- PubMed-not-MEDLINE
DCOM- 20200409
LR  - 20200421
IS  - 1424-8220 (Electronic)
IS  - 1424-8220 (Linking)
VI  - 20
IP  - 6
DP  - 2020 Mar 20
TI  - An Efficient Attribute-Based Access Control (ABAC) Policy Retrieval Method Based 
      on Attribute and Value Levels in Multimedia Networks.
LID - 10.3390/s20061741 [doi]
LID - 1741
AB  - Internet of Multimedia Things (IoMT) brings convenient and intelligent services 
      while also bringing huge challenges to multimedia data security and privacy. 
      Access control is used to protect the confidentiality and integrity of restricted 
      resources. Attribute-Based Access Control (ABAC) implements fine-grained control 
      of resources in an open heterogeneous IoMT environment. However, due to numerous 
      users and policies in ABAC, access control policy evaluation is inefficient, 
      which affects the quality of multimedia application services in the Internet of 
      Things (IoT). This paper proposed an efficient policy retrieval method to improve 
      the performance of access control policy evaluation in multimedia networks. 
      First, retrieve policies that satisfy the request at the attribute level by 
      computing based on the binary identifier. Then, at the attribute value level, the 
      depth index was introduced to reconstruct the policy decision tree, thereby 
      improving policy retrieval efficiency. This study carried out simulation 
      experiments in terms of the different number of policies and different policy 
      complexity situation. The results showed that the proposed method was three to 
      five times more efficient in access control policy evaluation and had stronger 
      scalability.
FAU - Liu, Meiping
AU  - Liu M
AUID- ORCID: 0000-0001-5298-1574
AD  - State Key Laboratory of Media Convergence and Communication, Communication 
      University of China, Beijing 100024, China.
AD  - School of Information and Communication Engineering, Communication University of 
      China, Beijing 100024, China.
FAU - Yang, Cheng
AU  - Yang C
AUID- ORCID: 0000-0003-3873-6411
AD  - State Key Laboratory of Media Convergence and Communication, Communication 
      University of China, Beijing 100024, China.
AD  - School of Information and Communication Engineering, Communication University of 
      China, Beijing 100024, China.
FAU - Li, Hao
AU  - Li H
AUID- ORCID: 0000-0002-9045-561X
AD  - Post-Doctoral Research Center of Zhuhai Da Hengqin Science and Technology 
      Development Co. Ltd., Zhuhai 519000, China.
FAU - Zhang, Yana
AU  - Zhang Y
AD  - State Key Laboratory of Media Convergence and Communication, Communication 
      University of China, Beijing 100024, China.
AD  - School of Information and Communication Engineering, Communication University of 
      China, Beijing 100024, China.
LA  - eng
GR  - CUC2019A009/Fundamental Research Funds for the Central Universities of the 
      Communication University of China/
GR  - CUC190J054/the High-quality and Cutting-edge Disciplines Construction Project for 
      Universities in Beijing(Internet Information,Communication University of China)/
GR  - CUC19ZD003/National Key Task Team Cultivation Project 2019/
PT  - Journal Article
DEP - 20200320
PL  - Switzerland
TA  - Sensors (Basel)
JT  - Sensors (Basel, Switzerland)
JID - 101204366
SB  - IM
PMC - PMC7147467
OTO - NOTNLM
OT  - ABAC
OT  - binary identifier
OT  - depth index
OT  - policy evaluation
OT  - policy retrieval
COIS- The authors declare no conflicts of interest.
EDAT- 2020/04/05 06:00
MHDA- 2020/04/05 06:01
PMCR- 2020/03/01
CRDT- 2020/04/05 06:00
PHST- 2020/01/09 00:00 [received]
PHST- 2020/02/27 00:00 [revised]
PHST- 2020/03/18 00:00 [accepted]
PHST- 2020/04/05 06:00 [entrez]
PHST- 2020/04/05 06:00 [pubmed]
PHST- 2020/04/05 06:01 [medline]
PHST- 2020/03/01 00:00 [pmc-release]
AID - s20061741 [pii]
AID - sensors-20-01741 [pii]
AID - 10.3390/s20061741 [doi]
PST - epublish
SO  - Sensors (Basel). 2020 Mar 20;20(6):1741. doi: 10.3390/s20061741.