Pantaleone Nespoli, Mattia Zago, Alberto Huertas Celdrán, Manuel Gil Pérez, Félix Gómez Mármol, Félix J. García Clemente
Special Issue on Sensor Systems for Internet of Things, Sensors, vol. 19, no. 12
Publication year: 2019

Abstract

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 still poses a number of 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 in order to include the above-mentioned component. Exhaustive experiments demonstrate the efficacy, feasibility and scalability of the proposed soluti

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Co-Authors

This work would not have been possible without the inestimable contribution of:

  • Pantaleone Nespoli
  • Mattia Zago
  • Alberto Huertas Celdrán
  • Manuel Gil Pérez
  • Félix J. García Clemente

Pantaleone Nespoli

Pantaleone Nespoli

University of Murcia

Web

Mattia Zago

Mattia Zago

University of Murcia

Web

Alberto Huertas Celdrán

Alberto Huertas Celdrán

University of Murcia

Web

Manuel Gil Pérez

Manuel Gil Pérez

University of Murcia

Web

Félix J. García Clemente

Félix J. García Clemente

University of Murcia

Web

Citation

Pantaleone Nespoli, Mattia Zago, Alberto Huertas Celdrán, Manuel Gil Pérez, Félix Gómez Mármol, Félix J. García Clemente, «PALOT: Profiling and Authenticating users Leveraging internet Of Things«, Special Issue on Sensor Systems for Internet of Things, Sensors, vol. 19, no. 12, 2019

Journal Ranking & Impact Factor

  • Journal: Sensors
  • Category: Instruments & Instrumentation
  • Rank: 15/61
  • Quartile: Q1
  • Impact Factor: 3.031