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Data Mining and privacy Presentation This is a sample presentation on data mining. The presetation looks at the critical Issues In Data Mining: Privacy, National Security And Personal Liberty Implications Of Data Mining

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CRITICAL ISSUES IN DATA MINING: PRIVACY, NATIONAL SECURITY AND PERSONAL LIBERTY IMPLICATIONS OF DATA MINING Name Lecturer Course Date By: https://www.essaypeer.com
THE INFERENCE PROBLEM By: https://www.essaypeer.com
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. By: https://www.essaypeer.com
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? By: https://www.essaypeer.com
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. By: https://www.essaypeer.com
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. By: https://www.essaypeer.com
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. By: https://www.essaypeer.com

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data mining privacy concerns ppt presentation

  • 1.
  • 2. CRITICAL ISSUES IN DATA MINING: PRIVACY, NATIONAL SECURITY AND PERSONAL LIBERTY IMPLICATIONS OF DATA MINING Name Lecturer Course Date By: https://www.essaypeer.com
  • 3. THE INFERENCE PROBLEM By: https://www.essaypeer.com
  • 4. 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. By: https://www.essaypeer.com
  • 5. 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? By: https://www.essaypeer.com
  • 6. 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. By: https://www.essaypeer.com
  • 7. 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. By: https://www.essaypeer.com
  • 8. 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. By: https://www.essaypeer.com

Editor's Notes

  1. I have been asked to select an article relating to data mining, predictive analytics and discovery informatics and describe the main concepts presented in the paper with a view of outlining the contributions that the paper or article has contributed to the field and I shall do that. The paper I choose is “Data Mining, National Security, Privacy and Civil Liberties “. The paper addresses the threats that data mining poses to privacy due to the inference problem and the how to handle the inference problem.
  2. The figure above shows the inference problem in data mining. Inference Is the process of posing queries to a database to get unauthorized information from the innocent responses received from authorized data. Databases are meant to provide access to group data while protecting the confidentiality of personal data. However, a skilled data miner can obtain from these databases information about individuals by correlating the different statistics given in a data base (Farkas and 2002 Jajodia).
  3. Since data mining is a threat to privacy, the challenge would be to protect the privacy of personal information, considering the social and legal precautions in place, and without undermining the ability of data mining to provide trends and timely information to users.
  4. The use of data mining brings with it serious questions on the privacy of personal information.
  5. Privacy enhanced data mining seeks to make available all the benefits that accrue due to the use of data mining in national security issues but at the same time enhance personal information
  6. The article shows the current privacy problems as the web becomes more and more sophisticated and as the need to gather intelligence for national security increases. It also discusses the inference problems and the possible ways to eliminate this problem.