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Open AccessArticle

False Data Detection for Fog and Internet of Things Networks

1
Department of Information Engineering, University of Florence, 50139 Firenze, Italy
2
Dipartimento di Elettronica e Informazione, Politecnico di Milano, 20133 Milano, Italy
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(19), 4235; https://doi.org/10.3390/s19194235
Received: 14 August 2019 / Revised: 19 September 2019 / Accepted: 28 September 2019 / Published: 29 September 2019
The Internet of Things (IoT) context brings new security issues due to billions of smart end-devices both interconnected in wireless networks and connected to the Internet by using different technologies. In this paper, we propose an attack-detection method, named Data Intrusion Detection System (DataIDS), based on real-time data analysis. As end devices are mainly resource constrained, Fog Computing (FC) is introduced to implement the DataIDS. FC increases storage, computation capabilities, and processing capabilities, allowing it to detect promptly an attack with respect to security solutions on the Cloud. This paper also considers an attack tree to model threats and vulnerabilities of Fog/IoT scenarios with heterogeneous devices and suggests countermeasure costs. We verify the performance of the proposed DataIDS, implementing a testbed with several devices that measure different physical quantities and by using standard data-gathering protocols. View Full-Text
Keywords: Internet of Things; security; dynamic protection; intelligence for embedded and cyber-physical systems; adaptive systems; fault detection and diagnosis; smart sensor networks Internet of Things; security; dynamic protection; intelligence for embedded and cyber-physical systems; adaptive systems; fault detection and diagnosis; smart sensor networks
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MDPI and ACS Style

Fantacci, R.; Nizzi, F.; Pecorella, T.; Pierucci, L.; Roveri, M. False Data Detection for Fog and Internet of Things Networks. Sensors 2019, 19, 4235.

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