@PhDThesis{	  2021moellers,
  address	= {Saarbrücken},
  author	= {Frederik M{\"o}llers},
  title		= {On privacy in home automation systems},
  school	= {Universität des Saarlandes},
  year		= {2021},
  type		= {{Dissertation}},
  abstract	= {Home Automation Systems (HASs) are becoming increasingly
		  popular in newly built as well as existing properties.
		  While offering increased living comfort, resource saving
		  features and other commodities, most current commercial
		  systems do not protect sufficiently against passive
		  attacks. In this thesis we investigate privacy aspects of
		  Home Automation Systems. We analyse the threats of
		  eavesdropping and traffic analysis attacks, demonstrating
		  the risks of virtually undetectable privacy violations. By
		  taking aspects of criminal and data protection law into
		  account, we give an interdisciplinary overview of privacy
		  risks and challenges in the context of HASs. We present the
		  first framework to formally model privacy guarantees of
		  Home Automation Systems and apply it to two different dummy
		  traffic generation schemes. In a qualitative and
		  quantitative study of these two algorithms, we show how
		  provable privacy protection can be achieved and how privacy
		  and energy efficiency are interdependent. This allows
		  manufacturers to design and build secure Home Automation
		  Systems which protect the users' privacy and which can be
		  arbitrarily tuned to strike a compromise between privacy
		  protection and energy efficiency.},
  url		= {https://publikationen.sulb.uni-saarland.de/bitstream/20.500.11880/31743/1/2021-08-09.pdf}
}