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2020-11-23
Awaysheh, F., Cabaleiro, J. C., Pena, T. F., Alazab, M..  2019.  Big Data Security Frameworks Meet the Intelligent Transportation Systems Trust Challenges. 2019 18th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/13th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE). :807–813.
Many technological cases exploiting data science have been realized in recent years; machine learning, Internet of Things, and stream data processing are examples of this trend. Other advanced applications have focused on capturing the value from streaming data of different objects of transport and traffic management in an Intelligent Transportation System (ITS). In this context, security control and trust level play a decisive role in the sustainable adoption of this trend. However, conceptual work integrating the security approaches of different disciplines into one coherent reference architecture is limited. The contribution of this paper is a reference architecture for ITS security (called SITS). In addition, a classification of Big Data technologies, products, and services to address the ITS trust challenges is presented. We also proposed a novel multi-tier ITS security framework for validating the usability of SITS with business intelligence development in the enterprise domain.