Applying Security to a Big Stream Cloud Architecture for the Internet of Things

Laura Belli, Simone Cirani, Luca Davoli, Gianluigi Ferrari, Lorenzo Melegari and Marco Picone
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Laura Belli: University of Parma, Parma, Italy
Simone Cirani: University of Parma, Parma, Italy
Luca Davoli: University of Parma, Parma, Italy
Gianluigi Ferrari: University of Parma, Parma, Italy
Lorenzo Melegari: University of Parma, Parma, Italy
Marco Picone: University of Parma, Parma, Italy

International Journal of Distributed Systems and Technologies (IJDST), 2016, vol. 7, issue 1, 37-58

Abstract: The Internet of Things (IoT) is expected to interconnect billions (around 50 by 2020) of heterogeneous sensor/actuator-equipped devices denoted as “Smart Objects” (SOs), characterized by constrained resources in terms of memory, processing, and communication reliability. Several IoT applications have real-time and low-latency requirements and must rely on architectures specifically designed to manage gigantic streams of information (in terms of number of data sources and transmission data rate). We refer to “Big Stream” as the paradigm which best fits the selected IoT scenario, in contrast to the traditional “Big Data” concept, which does not consider real-time constraints. Moreover, there are many security concerns related to IoT devices and to the Cloud. In this paper, we analyze security aspects in a novel Cloud architecture for Big Stream applications, which efficiently handles Big Stream data through a Graph-based platform and delivers processed data to consumers, with low latency. The authors detail each module defined in the system architecture, describing all refinements required to make the platform able to secure large data streams. An experimentation is also conducted in order to evaluate the performance of the proposed architecture when integrating security mechanisms.

Date: 2016
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