Title: Securing Manufacturing Intelligence for the Industrial Internet of Things,
Abstract: Widespread interest in the emerging area of predictive analytics is driving
industries such as manufacturing to explore new approaches to the collection
and management of data provided from Industrial Internet of Things (IIoT)
devices. Often, analytics processing for Business Intelligence (BI) is an
intensive task, and it also presents both an opportunity for competitive
advantage as well as a security vulnerability in terms of the potential for
losing Intellectual Property (IP). This article explores two approaches to
securing BI in the manufacturing domain. Simulation results indicate that a
Unified Threat Management (UTM) model is simpler to maintain and has less
potential vulnerabilities than a distributed security model. Conversely, a
distributed model of security out-performs the UTM model and offers more scope
for the use of existing hardware resources. In conclusion, a hybrid security
model is proposed where security controls are segregated into a multi-cloud
architecture.