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.

中文翻译：

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用于多数据中心环境中隐私保护的动态和语义感知访问控制模型

随着物联网中智能感知等数据采集技术的快速发展，大规模科学工作流被广泛应用于地理分布的多个数据中心，以实现业务模型构建和计算处理的高性能。然而，内部威胁对系统构成了非常重大的隐私和安全风险。在这些新的跨域环境中，传统的访问控制模型已经不能满足资源的合理授权。因此，提出了一种动态的、语义感知的访问控制模型，用于多数据中心环境下的隐私保护，该模型实现了基于用户行为序列异常评估的语义动态授权策略。