@InCollection{	  marnau19law,
  year		= {2022},
  editors	= {Gonz{\'a}lez-Fuster, Gloria and van Brakel, Rosamunde and
		  De Hert, Paul},
  booktitle	= {Research Handbook on Privacy and Data Protection Law:
		  Values, Norms and Global Politics},
  publisher	= {Edward Elgar Publishing},
  author	= {Ninja Marnau and Christoph Sorge},
  title		= {From Law to Engineering: A Computer Science Perspective on
		  Privacy \& Data Protection},
  pages		= {197--213},
  month		= {January},
  abstract	= {Privacy and data protection regulation tries to strike a
		  balance between legitimate data use and the right to
		  personal privacy. Nevertheless, the advances in computer
		  science pose new challenges to this careful balance.
		  Data-driven analytics as well as resulting data use and
		  business models e.g. for machine learning, big data and
		  automated decision-making threaten to make individuals,
		  their behaviour and their decision-making completely
		  transparent and predictable, deepening the power asymmetry
		  between individuals and data controllers.
		  
		  But the nature of computer science with regards to privacy
		  is Janus-faced. The ever-progressing digitalization also
		  requires digital solutions for effective privacy
		  protection. Computer science can and has to act as an
		  enabler of privacy-friendly data processing. The role of
		  privacy engineering and privacy-enhancing technologies by
		  far exceeds just guaranteeing legal compliance. In fact,
		  the crucial value of privacy engineering is to lessen the
		  latent conflict arising from this power asymmetry by
		  empowering the individual and building trust by giving
		  technical privacy assurances. In this chapter, we discuss
		  the core concepts of privacy engineering, provide some
		  examples of the state of the art, and discuss the relation
		  between privacy principles and technical measures.}
}