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Hacking your drone data
Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).
2021 (English)Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

The last couple of years has seen a rapid growth in smart devices. The smart devices are exponentially gaining more popularity both as a complement to our daily lives in the form of IoT products aiding in our everyday tasks and as a way we communicate and work. An estimation of 75.44 billion devices will be connected to the internet by 2025. With the rapid development and normalization of IoT devices, questions regarding privacy has never been more important. This thesis focuses on privacy in relation to one of the most emerging technologies, drones. 

Drones have been discussed frequently in both governmental and commercial sectors for its inevitable normalization in the airspace. Previously privacy and drones has been researched and discussed from the point of view of which drones are used to infringe on people’s privacy. This thesis explores privacy from another point of view, the view of the drone owner. By exploring privacy from the drone users’ point of view, this thesis shows the importance of better privacy measurements by proposing a conceptual model to existing popular privacy definitions. To investigate privacy in this context, a case has been conducted which proved and validated what kind of data is at risk of being hijacked. The thesis provides a conceptual model that aims to help commercial drone owners to analyze how privacy infringements can occur, why they could occur and how to account for them in the future. Furthermore, the thesis highlights the vulnerability that WIFI dependent devices poses with DDoS attacks. The findings of this thesis show that an infringement of privacy regarding commercial drones requires more clear privacy regulations and definitions, as well as highlighting privacy vulnerabilities in commercial drones. 

Place, publisher, year, edition, pages
2021. , p. 76
National Category
Other Engineering and Technologies not elsewhere specified
Identifiers
URN: urn:nbn:se:mau:diva-41403OAI: oai:DiVA.org:mau-41403DiVA, id: diva2:1539336
Educational program
TS Computer Science, Master Programme
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Available from: 2021-03-23 Created: 2021-03-23 Last updated: 2021-03-23Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
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  • de-DE
  • en-GB
  • en-US
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  • nn-NO
  • nn-NB
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  • Other locale
More languages
Output format
  • html
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