Abstract
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.
Highlights
With the development and application of data acquisition equipment and technology in the Internet of things, the joint use of multiple data centers is regarded as essential for many online services.[1]
Europe’s General Data Protection Regulation (GDPR) requires data center users to focus on privacy.[2]
A dynamic and semantic-aware access-control (DSAAC) model that is based on sequence anomaly evaluation is proposed by considering the characteristics of the workflow in a multiple data center environment
Summary
With the development and application of data acquisition equipment and technology in the Internet of things, the joint use of multiple data centers is regarded as essential for many online services.[1]. In Crampton and Huth,[4] a new access-control architecture was formulated, the realization of which might form part of an overall strategy for addressing the insider problem In this architecture, trustworthiness and risk-assessment methodologies were combined and extended in traditional role-based access control. Cross-center data processing applications are typically implemented as workflows,[5] which renders the access-control-based privacy protection more complicated. A dynamic and semantic-aware access-control (DSAAC) model that is based on sequence anomaly evaluation is proposed by considering the characteristics of the workflow in a multiple data center environment.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have