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Open AccessArticle

PALOT: Profiling and Authenticating Users Leveraging Internet of Things

1
Department of Information and Communications Engineering, University of Murcia, 30100 Murcia, Spain
2
Telecommunication Software & Systems Group, Waterford Institute of Technology, X91 K0EK Waterford, Ireland
3
Department of Computer Engineering and Technology, University of Murcia, 30100 Murcia, Spain
*
Authors to whom correspondence should be addressed.
Sensors 2019, 19(12), 2832; https://doi.org/10.3390/s19122832
Received: 23 May 2019 / Revised: 17 June 2019 / Accepted: 19 June 2019 / Published: 25 June 2019
(This article belongs to the Special Issue Sensor Systems for Internet of Things)
Continuous authentication was introduced to propose novel mechanisms to validate users’ identity and address the problems and limitations exposed by traditional techniques. However, this methodology poses several challenges that remain unsolved. In this paper, we present a novel framework, PALOT, that leverages IoT to provide context-aware, continuous and non-intrusive authentication and authorization services. To this end, we propose a formal information system model based on ontologies, representing the main source of knowledge of our framework. Furthermore, to recognize users’ behavioral patterns within the IoT ecosystem, we introduced a new module called “confidence manager”. The module is then integrated into an extended version of our early framework architecture, IoTCAF, which is consequently adapted to include the above-mentioned component. Exhaustive experiments demonstrated the efficacy, feasibility and scalability of the proposed solution. View Full-Text
Keywords: continuous authentication; IoT; authorization; security; behavioral patterns discovery; Markov Model continuous authentication; IoT; authorization; security; behavioral patterns discovery; Markov Model
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Nespoli, P.; Zago, M.; Huertas Celdrán, A.; Gil Pérez, M.; Gómez Mármol, F.; García Clemente, F.J. PALOT: Profiling and Authenticating Users Leveraging Internet of Things. Sensors 2019, 19, 2832.

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