A Secure Connectivity Model for Internet of Things Analytics Service Delivery

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Approaches to the provision of data analytics for businesses offer methods to analyse and model data, enabling informed decision making to improve business performance and profitability. Typically, analytics processing is an intensive task and the demand for business insight, on-demand, means that organisations make use of elastic cloud provisioned resources to host such services. However, within the shared domains of multi-tenant cloud computing, business data and models are exposed to greater security threats and compromised privacy, since an unauthorised user may be able to gain access to highly sensitive, consolidated business-critical information. Business analytics processes are often composed from orchestrated, collaborating services, which are consumed by users from multiple cloud systems (in different security realms), which need to be engaged dynamically at runtime. If heterogeneous cloud systems located in different security realms do not have direct
authentication relationships, then it is a considerable technical challenge to enable secure collaboration. In order to address this security challenge, a new authentication framework is required to establish trust amongst business analytics service instances and users by distributing a common session secret to all participants of a session. We address this challenge by designing and implementing a secure multiparty authentication framework for dynamic interaction, for the scenario where members of different security realms express a need to access orchestrated services. This novel framework exploits the relationship of trust between session members in different security realms, to enable a user to obtain security credentials that access cloud resources in a remote realm. The mechanism assists cloud session users to authenticate their session membership, thereby improving the performance of authentication processes within multiparty sessions. We see applicability of this framework beyond multiple cloud infrastructure, to that of any scenario where multiple security realms has the potential to exist, such as the emerging Internet of Things (IoT).
Original languageEnglish
Title of host publication2018 IEEE Smart World, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI)
EditorsFrederic Loulergue, Guojun Wang, Md Zakirul Alam Bhuiyan, Xiaoxing Ma, Peng Li, Manuel Roveri, Qi Han, Lei Chen
PublisherIEEE Computer Society
Pages9-16
Number of pages8
ISBN (Electronic)9781538693803
ISBN (Print)9781538693810
DOIs
Publication statusPublished - 4 Dec 2018
Externally publishedYes
Event2018 IEEE Smart World Congress: Ubiquitous Intelligence for Smart World - Guangzhou, China
Duration: 8 Oct 201812 Oct 2018
http://www.smart-world.org/2018/ (Link to Conference Website)

Conference

Conference2018 IEEE Smart World Congress
CountryChina
CityGuangzhou
Period8/10/1812/10/18
Internet address

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Cite this

Al-Aqrabi, H., & Hill, G. (2018). A Secure Connectivity Model for Internet of Things Analytics Service Delivery. In F. Loulergue, G. Wang, M. Z. A. Bhuiyan, X. Ma, P. Li, M. Roveri, Q. Han, ... L. Chen (Eds.), 2018 IEEE Smart World, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI) (pp. 9-16). [8560016] IEEE Computer Society. https://doi.org/10.1109/SmartWorld.2018.00038