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Abstract
The main aim of the thesis is to propose AntibIoTic 2.0, a distributed system that relies on Fog computing to secure the Internet of Things. The Internet of Things (IoT) can be defined as a network of computing devices capable of exchanging data over the Internet without human intervention. Today, these smart devices have become pervasive and increasingly employed in consumer, organisational, industrial, infrastructure, and military applications. While creating new business opportunities and offering enhanced services to the users, the IoT revolution poses a severe threat to the global Internet security, as proven by the high number of attacks sourced from IoT malware over the last years. The result is a surge of interest in the IoT security, leading to novel technologies and paradigms, such as Fog computing. Fog computing is a novel distributed paradigm introduced as an extension of Cloud computing to bridge the gap between Cloud and IoT while offering a number of services, including security. In this thesis, we investigate the Cloud-to-Thing continuum and propose AntibIoTic 2.0, a distributed solution that relies on Fog computing to secure the Internet of Things. First, we introduce the motivation behind this work, analysing Distributed Denial of Service (DDoS) attacks and IoT malware, and presenting AntibIoTic 1.0 with its limitations. Then, we investigate the literature on Fog computing, Cloud computing, and IoT, with a focus on the security aspects. Finally, we use this analysis as a source of knowledge and inspiration to design, implement, and evaluate AntibIoTic 2.0, the main and final contribution of this dissertation.
Original language | English |
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Publisher | Technical University of Denmark |
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Number of pages | 246 |
Publication status | Published - 2020 |
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Security in Fog Computing
De Donno, M. (PhD Student), Conti, M. (Examiner), Di Pietro, R. (Examiner), Pop, P. (Examiner), Dragoni, N. (Main Supervisor) & Fafoutis, X. (Supervisor)
Technical University of Denmark
01/09/2017 → 13/01/2021
Project: PhD