2019/01/22 by Hussain Al-Aqrabi, Richard Hill, Al-Aqrabi, Hussain +5
Business, Management and Accounting · Computer Science · Engineering · #Big Data and Business Intelligence #Cryptography and Security (cs.CR) #Digital Transformation in Industry #FOS: Computer and information sciences #Physical Unclonable Functions (PUFs) and Hardware Security
paper · pdf · doi:10.48550/arxiv.1901.07284
openalex publication_date 2019/01/22 · openalex created_date 2022/07/30 · openalex updated_date 2026/07/28
Widespread interest in the emerging area of predictive analytics is driving\nindustries such as manufacturing to explore new approaches to the collection\nand management of data provided from Industrial Internet of Things (IIoT)\ndevices. Often, analytics processing for Business Intelligence (BI) is an\nintensive task, and it also presents both an opportunity for competitive\nadvantage as well as a security vulnerability in terms of the potential for\nlosing Intellectual Property (IP). This article explores two approaches to\nsecuring BI in the manufacturing domain. Simulation results indicate that a\nUnified Threat Management (UTM) model is simpler to maintain and has less\npotential vulnerabilities than a distributed security model. Conversely, a\ndistributed model of security out-performs the UTM model and offers more scope\nfor the use of existing hardware resources. In conclusion, a hybrid security\nmodel is proposed where security controls are segregated into a multi-cloud\narchitecture.\n