Risk based access control in cloud computing

H, Lakshmi; Namitha, S; Seemanthini,; Gopalan, S. Harihara; Sanjay, H. A.; K, Chandrashekaran; Bhaskar, Atul

doi:10.1109/icgciot.2015.7380704

Cited by 5 publications

(1 citation statement)

References 3 publications

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“…Lakshmi et al proposed a model for the identification of insider attackers by adjusting the session based on risk assessment. 20,21 Fall et al 22 also proposed a risk-adaptive authorization mechanism to satisfy the dynamicity in the cloud environment.…”

Section: Related Workmentioning

confidence: 99%

Dynamic and semantic-aware access-control model for privacy preservation in multiple data center environments

Chen

Xing

et al. 2020

International Journal of Distributed Sensor Networks

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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.

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Section: Related Workmentioning

confidence: 99%