Access Control Policy of Data Considering Varying Context in Sensor Fusion Environment of Internet of Things

Autor: You Jin Song, Jae Kyu Lee, Yei Chang Kim, Aria Seo
Rok vydání: 2015
Předmět:
Zdroj: KIPS Transactions on Software and Data Engineering. 4:409-418
ISSN: 2287-5905
DOI: 10.3745/ktsde.2015.4.9.409
Popis: In order to delivery of the correct information in IoT environment, it is important to deduce collected information according to a user's situation and to create a new information. In this paper, we propose a control access scheme of information through context-aware to protect sensitive information in IoT environment. It focuses on the access rights management to grant access in consideration of the user's situation, and constrains(access control policy) the access of the data stored in network of unauthorized users. To this end, after analysis of the existing research 'CP-ABE-based on context information access control scheme', then include dynamic conditions in the range of status information, finally we propose a access control policy reflecting the extended multi-dimensional context attribute. Proposed in this paper, access control policy considering the dynamic conditions is designed to suit for IoT sensor fusion environment. Therefore, comparing the existing studies, there are advantages it make a possible to ensure the variety and accuracy of data, and to extend the existing context properties.Keywords:Internet of Things, Sensor Fusion, Context Awareness, Access Control Policy, Access Structure Tree
Databáze: OpenAIRE