期刊名称：International Journal of Distributed Sensor Networks
印刷版ISSN：1550-1329
电子版ISSN：1550-1477
出版年度：2020
卷号：16
期号：5
页码：1
DOI：10.1177/1550147720921778
出版社：Hindawi Publishing Corporation
摘要：With the rapid development of intelligent perception and other data acquisition technologies in the Internet of things, large-scale scientific workflows have been widely used in geographically distributed multiple data centers to realize high performance in business model construction and computational processing. However, insider threats pose very significant privacy and security risks to systems. Traditional access-control models can no longer satisfy the reasonable authorization of resources in these new cross-domain environments. Therefore, a dynamic and semantic-aware access-control model is proposed for privacy preservation in multiple data center environments, which implements a semantic dynamic authorization strategy based on an anomaly assessment of users’ behavior sequences. The experimental results demonstrate that this dynamic and semantic-aware access-control model is highly dynamic and flexible and can improve the security of the application system.
