Securing Manufacturing Intelligence for the Industrial Internet of Things
This addresses security vulnerabilities in manufacturing data analytics for industries using IIoT, though it appears incremental as it builds on existing security models.
The paper tackles securing business intelligence analytics in manufacturing IIoT systems by comparing unified threat management and distributed security models, finding that UTM is simpler with fewer vulnerabilities while distributed models perform better and utilize hardware more efficiently, leading to a proposed hybrid multi-cloud architecture.
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.