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Why Privacy?
Discipline Specificity
Problem
● Research across disciplines suffers because
there is no unifed mechanism for measurement
● Computer science has focussed on policy
enforcement, ontologies and taxonomies
● Nobody looks at individual privacy preferences
in a given environment, which is the basis for
legislation
– And also how requirements must be derived
2 Examples
● Facebook
● Twitter
People on Facebook
People on Facebook
Versus
Hypothesis
● Disregarding the value-based approach to
privacy, it's possible to dervie a finite
representation based on discrete factors
● The representation can be used to understand
privacy betteracross disciplines
– Standardization
– Measurement
– Management
Theoretical Framework
● Scientific / mathematical determinism
● Plus.
The States
1)Private: existence is unknown
2)Unidentified: presence is known
3)Anonymous: information known but no identity
4)Masked: identity linkage is concealed
5)De-identified: identity is not directly linked
6)Pseudonymous: identity is falsefied
7)Confidential: identity is known for a specific purpose
8)Identified: capable of being distinguised
9)Public: everything is known and assigned
Factors
● Human: considerations when privacy decisions
are made
● Technology: services that computers perform
related to information management
● Data Types: types of identifiable information
● Recepient: machine v. human
● Architecture: characteristics of the physical
environment
Human
● Human privacy rules are specific to the establishment;
they are reflected in the physical structure and
properties of society
● Each individual has a social contact threshold which
determines how they exercise their privacy rights
● Examples:
● Subject matter of the object
● Control of disclosure, information, audience
● Social structure and condition
● Visibility
● Expectations
Data Types
● Notion of privacy as information protection is
well represented in legislaiton and regulation
across the world
● Less widely used is the notion of identifiability:
that data exists that may or may not include the
traditional identifiers, e.g. Name, but may still
uniquely identify a person
● What is more private: a phone number or a
prescription?
Technology
● Computers are generally accepted to be an effective tool
for information management; used to acquire, organize,
retrieve, search and maintain information
● This happens increasingly without human intervention
● When it comes to managing information about an
identifiable person, there are a discrete number of
functions that computers can provide
● Examples:
● Network, hosting, registration, mail, website/portal, software,
backup
Proposed Formalization
1) Sn = w H f (H )+ wD f (D)+ wT f (T )
2) f (Factor) = (w1F1 + w2 F2 +... + wn Fn )
3) The more positive the individual factors, the
higher to total result of the factor set, the more
likely the individual will move to a lower state of
privacy, Sm>Sn
Transitions
● Forward
● I disclose about me, my objects
● You disclose about me, my objects
● Backward
● information redaction
● information protection
Questions For You
● How do people make decisions?
● Specifically in social situations?
● How does space change behaviour?
● Any suggestions for testing?
● What are the other disciplines that talk about
space, privacy, representation of self?
● Suggestions on theoretical frameworks?
An Offer

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Kosa - Theory for Privacy Measuring v2

  • 1.
  • 2.
  • 3.
  • 4.
  • 5.
  • 6.
  • 7.
  • 8.
  • 9.
  • 10.
  • 11.
  • 14.
  • 15.
  • 16.
  • 17. Problem ● Research across disciplines suffers because there is no unifed mechanism for measurement ● Computer science has focussed on policy enforcement, ontologies and taxonomies ● Nobody looks at individual privacy preferences in a given environment, which is the basis for legislation – And also how requirements must be derived
  • 21.
  • 22.
  • 24.
  • 25.
  • 26. Hypothesis ● Disregarding the value-based approach to privacy, it's possible to dervie a finite representation based on discrete factors ● The representation can be used to understand privacy betteracross disciplines – Standardization – Measurement – Management
  • 27. Theoretical Framework ● Scientific / mathematical determinism ● Plus.
  • 28. The States 1)Private: existence is unknown 2)Unidentified: presence is known 3)Anonymous: information known but no identity 4)Masked: identity linkage is concealed 5)De-identified: identity is not directly linked 6)Pseudonymous: identity is falsefied 7)Confidential: identity is known for a specific purpose 8)Identified: capable of being distinguised 9)Public: everything is known and assigned
  • 29.
  • 30. Factors ● Human: considerations when privacy decisions are made ● Technology: services that computers perform related to information management ● Data Types: types of identifiable information ● Recepient: machine v. human ● Architecture: characteristics of the physical environment
  • 31. Human ● Human privacy rules are specific to the establishment; they are reflected in the physical structure and properties of society ● Each individual has a social contact threshold which determines how they exercise their privacy rights ● Examples: ● Subject matter of the object ● Control of disclosure, information, audience ● Social structure and condition ● Visibility ● Expectations
  • 32. Data Types ● Notion of privacy as information protection is well represented in legislaiton and regulation across the world ● Less widely used is the notion of identifiability: that data exists that may or may not include the traditional identifiers, e.g. Name, but may still uniquely identify a person ● What is more private: a phone number or a prescription?
  • 33. Technology ● Computers are generally accepted to be an effective tool for information management; used to acquire, organize, retrieve, search and maintain information ● This happens increasingly without human intervention ● When it comes to managing information about an identifiable person, there are a discrete number of functions that computers can provide ● Examples: ● Network, hosting, registration, mail, website/portal, software, backup
  • 34. Proposed Formalization 1) Sn = w H f (H )+ wD f (D)+ wT f (T ) 2) f (Factor) = (w1F1 + w2 F2 +... + wn Fn ) 3) The more positive the individual factors, the higher to total result of the factor set, the more likely the individual will move to a lower state of privacy, Sm>Sn
  • 35. Transitions ● Forward ● I disclose about me, my objects ● You disclose about me, my objects ● Backward ● information redaction ● information protection
  • 36. Questions For You ● How do people make decisions? ● Specifically in social situations? ● How does space change behaviour? ● Any suggestions for testing? ● What are the other disciplines that talk about space, privacy, representation of self? ● Suggestions on theoretical frameworks?