Approximate Information Flows (AIF)

Xiaodong Jiang, Jason I. Hong, and James A. Landay, apply different concepts from economics and information theory to model the exchange of information among the different actors (data owners, data collectors and data users) to minimize the asymmetry of information flow among them.

Approximate Information Flows Diagram

After identifying the main actors they propose the principle of minimum asymmetry:

 Principle of Minimum Asymmetry

A privacy-aware system should minimize the asymmetry of information between data owners and data collectors and data users, by:

  • Decreasing the flow of information from data owners to data collectors and users
  • Increasing the flow of information from data collectors and users back to data owners

To support this Principle of Minimum Asymmetry they design a space of Privacy solutions in Ubiquitous Computing


X. Jiang, J. I. Hong, and J. A. Landay, “Approximate information flows: Socially-based modeling of privacy in ubiquitous computing,”

The Seven Types of Privacy

Rachel L. Finn , David Wright , and Michael Friedewald elaborated a really interesting list of categories of privacy related issues caused by the improvements in different types of technology.

  • The Physical Person: This category refers specifically to aspects of the human body, for example: nudity, biometric data, electronic implants and sensing devices, brain signals monitors and any other type of information related to the physical body.
  • Behavior and Action: Any type of information that reflects aspects of a person’s lifestyle, for example: Sexuality, religion, political beliefs or habits.
  • Personal Communications: From traditional wiretap to more advanced email interception or capture and analysis of text from messaging apps like WhatsApp or Facebook.
  • Data and Image: Problems derived from the proliferation of surveillance cameras or the appearance of massive amounts of images and videos in the social networks together with the possibility to apply automated face recognition techniques.
  • Thoughts and Feelings: Technology can be used to estimate people’s mental state by using face/voice/gesture analysis.
  • Location and Space: Related to the information of someone’s location, be it obtained from GPS tracking, cameras surveillance, wifi/bluetooth spoofing.
  • Association and Group Membership: Privacy issues derived from aspects such as belonging to a specific community, following certain groups, individuals or initiatives in the social networks etc.