Trusted Compliance Enforcement Framework for Sharing Health Big Data

Kim, Dae-Young; Elluri, Lavanya; Joshi, Karuna Pande

doi:10.1109/bigdata52589.2021.9671834

Cited by 1 publication

(1 citation statement)

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“…It also incorporated roles, users, allowed operations (read or write), rescue missions in which users or organizations are involved, tasks in the mission, and others. A more sophisticated Contact Tracing ontology was proposed in [10]- [12] which contains slightly different classes such as electronic health records (EHR), travel history, and healthcare-related organizations and shared a similar structure with SAR ontology. However, all these works only considered behavioral trust based on policy compliance for access control.…”

Section: Related Workmentioning

confidence: 99%

MATS: A Multi-aspect and Adaptive Trust-based Situation-aware Access Control Framework for Federated Data-as-a-Service Systems

Kim

Alodadi

Chen

et al. 2022

2022 IEEE International Conference on Services Computing (SCC)

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Federated Data-as-a-Service systems are helpful in applications that require dynamic coordination of multiple organizations, such as maritime search and rescue, disaster relief, or contact tracing of an infectious disease. In such systems it is often the case that users cannot be wholly trusted, and access control conditions need to take the level of trust into account. Most existing work on trust-based access control in web services focuses on a single aspect of trust, like user credentials, but trust often has multiple aspects such as users' behavior and their organization. In addition, most existing solutions use a fixed threshold to determine whether a user's trust is sufficient, ignoring the dynamic situation where the trade-off between benefits and risks of granting access should be considered. We have developed a Multi-aspect and Adaptive Trust-based Situation-aware Access Control Framework we call "MATS" for federated data sharing systems. Our framework is built using Semantic Web technologies and uses game theory to adjust a system's access decisions based on dynamic situations. We use query rewriting to implement this framework and optimize the system's performance by carefully balancing efficiency and simplicity. In this paper we present this framework in detail, including experimental results that validate the feasibility of our approach.

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Section: Related Workmentioning

confidence: 99%