Data Mining and privacy Presentation

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Critical Issues In Data Mining Privacy,
National Security And Personal Liberty
Implications Of Data Mining

• Name
• Lecturer
• Course
• Date

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The Inference Problem
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Privacy issues Of Data Mining

• Information available freely on the internet
  being used illegitimately against the person.
• The social aspect of data mining privacy
  considering that different groups have different
  standards on social
• The legal an political aspects including controls
  on the web and servers, the consequences of
  violating privacy policies and transfer of
  information between countries.

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Civil liberties V.s National Security

• Civil liberty involves everything from
  pro0tecting the rights of individuals, be they
  human, civil or privacy rights. Gathering
  information about people, mining data about them,
  surveillance on personal conversations may result
  in violation of their rights to privacy.
• The main concern is whether to gather information
  and prosecute when violation on privacy occurs or
  wait until the national disasters occurs to
  gather data.
• Among the questions that arise include
• Is it worth sacrificing privacy to ensure some
  level of national security assuming the
  information is not misused?
• Should national security be placed first and then
  prosecute those who violate privacy if its not
  possible to safeguard this private information?

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Privacy Enhanced Data Mining And National Security

• Since national security is very important to most
  nations in view of the terrorism activity the
  world over, one of the way to ensure privacy of
  personal information is through sensitive data
  mining.
• Here, data mining is allowed but under enhanced
  privacy protection measures
• Sensitive data mining involves determining, in
  advance those patterns are private and which are
  public since patterns are what constitutes the
  inference problem.

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Solving the inference problem

• Bhavani Thuraisingham (2002) proposes the
  following measures to deal with the inference
  problem in data mining
• Build an inference controller that detect
  possible inference problems by a user and
  restricting the use of those patterns
• The other strategy would be to classify the
  information such that the user would not be
  confident in the results and will therefore find
  the inferences made useless.
• Lastly, the person holding the data can test the
  data to see if any inferences can be made using
  the data. However, this approach is limited
  because on cannot predict all the inferences that
  could be made from the data or the combinnation
  of tools that will be used in data mining to get
  these inferences.

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References

• Farkas, C., Jajodia, S. (2002). The Inference
  Problem A Survey. Center for Secure Information
  Systems , Fairfax, VA.
• Thuraisingham, B. (2005). Data Mining, National
  Security, Privacy and Civil Liberties. Arlington,
  VA Mendeley Ltd.

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