Title

AZSPM: autonomic zero-knowledge security provisioning model for medical control systems in fog computing environments

Document Type

Conference Proceeding

Publisher

IEEE

School

Security Research Institute

RAS ID

25401

Comments

Originally published as: Chaudhry, J., Saleem, K., Islam, R., Selamat, A., Ahmad, M., & Valli, C. (2017). AZSPM: Autonomic zero-knowledge security provisioning model for medical control systems in fog computing environments. Paper presented at the Proceedings - 2017 IEEE 42nd Conference on Local Computer Networks Workshops, LCN Workshops 2017, 121-127. Original article available here

Abstract

The panic among medical control, information, and device administrators is due to surmounting number of high-profile attacks on healthcare facilities. This hostile situation is going to lead the health informatics industry to cloud-hoarding of medical data, control flows, and site governance. While different healthcare enterprises opt for cloud-based solutions, it is a matter of time when fogcomputing environment are formed. Because of major gaps in reported techniques for fog security administration for health data i.e. absence of an overarching certification authority (CA), the security provisioning is one of the the issue that we address in this paper. We propose a security provisioning model (AZSPM) for medical devices in fog environments. We propose that the AZSPM can be build by using atomic security components that are dynamically composed. The verification of authenticity of the atomic components, for trust sake, is performed by calculating the processor clock cycles from service execution at the resident hardware platform. This verification is performed in the fully sand boxed environment. The results of the execution cycles are matched with the service specifications from the manufacturer before forwarding the mobile services to the healthcare cloud-lets. The proposed model is completely novel in the fog computing environments. We aim at building the prototype based on this model in a healthcare information system environment.

DOI

10.1109/LCN.Workshops.2017.73

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