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Vulnerability assessment of IoT-based Smart Lighting Systems
University of Skövde, School of Informatics.
2022 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

This study addresses the significant gap in literature regarding the security risks of smart lighting systems integrated within the Internet of Things (IoT) in commercial-industrial buildings. Utilizing the OCTAVE Allegro methodol-ogy(Caralli, Stevens, Young, & Wilson, 2007), a thorough risk assessment was performed, focusing on four main information assets: sensor data, sensors and their controllers, the centralized control server data of the Smart Lighting Sys-tems (SLS), and device identifiers and authentication credentials.Threats and impacts related to each asset were identified, revealing a set of vul-nerabilities inherent in the use of smart lighting systems. Concurrently, the study proposes countermeasures, which include robust technical controls, reg-ular security audits, user awareness programs, redundancy systems, and intru-sion detection mechanisms.The findings of this research underscore the potential for mitigating the secu-rity risks associated with smart lighting systems in commercial-industrial set-tings, thereby fostering a more secure and reliable implementation of these sys-tems. The conclusions drawn serve as a springboard for further research in en-hancing the security of smart lighting systems within the IoT ecosystem.

Place, publisher, year, edition, pages
2022. , p. 75
National Category
Information Systems
Identifiers
URN: urn:nbn:se:his:diva-23660OAI: oai:DiVA.org:his-23660DiVA, id: diva2:1844550
Subject / course
Informationsteknologi
Educational program
Privacy, Information and Cyber Security - Master's Programme 120 ECTS
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Examiners
Available from: 2024-03-14 Created: 2024-03-14 Last updated: 2024-03-14Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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  • ieee
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