Thesis (Selection of subject)Thesis (Selection of subject)(version: 285)
Assignment details
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Privacy issues of the Internet of Things
Thesis title in Czech: Privacy issues of the Internet of Things
Thesis title in English: Privacy issues of the Internet of Things
English key words: internet of things, privacy, privacy issues, privacy patterns, privacy in the internet of things
Academic year of topic announcement: 2015/2016
Type of assignment: diploma thesis
Thesis language: angličtina
Department: Department of Distributed and Dependable Systems (32-KDSS)
Supervisor: doc. RNDr. Tomáš Bureš, Ph.D.
Author: hidden - assigned and confirmed by the Study Dept.
Date of registration: 19.02.2016
Date of assignment: 28.02.2016
Confirmed by Study dept. on: 03.03.2016
Date and time of defence: 16.06.2016 10:00
Date of electronic submission:24.04.2016
Date of submission of printed version:28.04.2016
Date of proceeded defence: 16.06.2016
Reviewers: RNDr. Jan Kofroň, Ph.D.
 
 
 
Guidelines
The Internet of Things is the network of sensors, smart devices and, in general, any items embedded with electronics connected to the Internet. The IoT at large then allow collection and analysis of data from the IoT devices and offers control and useful insights in the data together with comparison and social sharing. This brings important challenges connected to privacy.

The subject of the thesis is to explore use cases of the internet of things and identify privacy issues. Then a set of best practices and guidelines to address these issues from the perspective of software architectures should be created. The final part of the thesis is to verify that these recommendations can be practically used. The thesis will come up with an idea how to implement them and will create proof of concept using one particular problem.
References
[1] Ying, Jian, et al. Protecting Receiver-Location Privacy in Wireless. University of Florida. [Online] 2007. http://www.cise.ufl.edu/~sgchen/paper/infocom07a.pdf

[2] Byun, Ji-Won, et al. The University of Texas at Dallas. Efficient k-Anonymization Using Clustering. [Online] http://www.utdallas.edu/~muratk/courses/privacy08f_files/proj_files/Efficient%20k-Anonymization%20Using%20Clustering%20Techniques.pdf

[3] Popa, Ada, Balakrishnan, Hari and Blumberg, Andrew J. VPriv: Protecting Privacy in Location-Based Vehicular Services. Standford. [Online] http://math.stanford.edu/~blumberg/traffic/vpriv.pdf

[4] Microsoft. https://azure.microsoft.com/en-us/documentation/services/iot-hub/. Microsoft Azure. [Online]
 
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