An Attribute-Based Access Control Policy Retrieval Method Based on Binary Sequence

With the widespread application of new technologies, fine-grained authorization requires a large number of access control policies. However, the existing policy retrieval method applied to a large-scale policy environment has the problem of low retrieval efficiency. Therefore, this paper proposes an attribute access control policy retrieval method based on the binary sequence. This method uses binary identification and binary code to express access control requests and policies. When the policy is retrieved, the appropriate group is selected through the logical operation of the access control request and the policy binary identification. Within the group, the binary code of the access control request is matched with the binary code of all rules to find suitable rules, thereby reducing the number of matching attribute-value pairs in the rule and improving the efficiency of policy retrieval. Experimental results show that the policy retrieval method proposed in this paper has higher retrieval efficiency.

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A Trust-Aware Access Control Policy for Cloud Data Protection

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.411-414.40 ◽

2013 ◽

Vol 411-414 ◽

pp. 40-44

Author(s):

Xiao Yong Tang ◽

Jin Wei Li ◽

Gui Ping Liao

Keyword(s):

Cloud Computing ◽

Access Control ◽

Data Privacy ◽

Large Scale ◽

Control Policy ◽

Trust Model ◽

Data Encryption ◽

Access Control Policy ◽

Cloud Users ◽

Cloud User

The use of Cloud computing systems to run large-scale scientific, business and consumer based IT applications has increased rapidly in recent years. More and more Cloud users concern the data privacy protection and security in such systems. A natural way to tackle this problem is to adopt data encryption and access control policy. However, this solution is inevitably introduced a heavy computation overhead. In this paper, we first establish a trust model between Cloud servers and Cloud users. Then, we build the trust-aware attribute-based access control policies according to Cloud user trust level and Cloud request attributes. This technique can give different encryption and decryption data to Cloud user and substantive reduce the computation overhead of Cloud computing.

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Efficient Binary-Encoding Access Control Policy Combination for Large-Scale Collaborative Scenarios

2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE) ◽

10.1109/trustcom/bigdatase.2018.00085 ◽

2018 ◽

Author(s):

Chunhua Li ◽

Weirui Xie ◽

Ke Zhou

Keyword(s):

Access Control ◽

Large Scale ◽

Control Policy ◽

Access Control Policy ◽

Binary Encoding

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An Efficient Attribute-Based Access Control (ABAC) Policy Retrieval Method Based on Attribute and Value Levels in Multimedia Networks

Sensors ◽

10.3390/s20061741 ◽

2020 ◽

Vol 20 (6) ◽

pp. 1741 ◽

Cited By ~ 2

Author(s):

Meiping Liu ◽

Cheng Yang ◽

Hao Li ◽

Yana Zhang

Keyword(s):

Access Control ◽

Policy Evaluation ◽

Control Policy ◽

Policy Decision ◽

Multimedia Data ◽

Security And Privacy ◽

Multimedia Networks ◽

Access Control Policy ◽

Retrieval Method ◽

Attribute Based Access Control

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.

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