L. F. Cranor (Ed.) Special Issue on Internet Privacy. Communications of the ACM, 42(2), February 1999. Home/Search Document Not in Database Summary ACM TOC Related Articles Check |
This paper is cited in the following contexts:
Privacy Preserving Mining of Association Rules - Evfimievski, Srikant.. (2002) (48 citations) (Correct)
.... dramatic and escalating increase in digital data, concerns about privacy of personal information have emerged globally [15] 17] 20] 24] Privacy issues are further exacerbated now that the internet makes it easy for the new data to be automatically collected and added to databases [10] 13] [14] [27] 28] 29] The concerns over massive collection of data are naturally extending to analytic tools applied to data. Data mining, with its promise to efficiently discover valuable, non obvious information from large databases, is particularly vulnerable to misuse [11] 16] 20] 23] An ....
L. F. Cranor, editor. Special Issue on Internet Privacy. Comm. ACM, 42(2), Feb. 1999.
On the Design and Quantification of Privacy Preserving Data.. - Agrawal, Aggarwal (2001) (45 citations) (Correct)
....In particular, data mining techniques are considered a challenge to privacy preservation due to their natural tendency to use sensitive information about individuals. Some interesting discourses on the nature of privacy in the context of recent trends in information technology may be found in [3, 5, 10, 11, 12, 13]. This has lead to a considerable amount of focus on privacy preserving data collection and mining methods [1, 6, 7, 8, 15] An innovative approach for privacy preserving data mining was recently proposed in [1] This technique relies on two facts: # Users are not equally protective of all values ....
L. F. Cranor. Special issue on internet privacy. Communications of the ACM, 42(2), 1999.
Privacy-Preserving Data Mining - Agrawal, Srikant (2000) (98 citations) (Correct)
.... data, concerns about informational privacy have emerged globally [Tim97] Eco99] eu998] Off98] Privacy issues are further exacerbated now that the World Wide Web makes it easy for the new data to be automatically collected and added to databases [HE98] Wes98a] Wes98b] Wes99] CRA99a] Cra99b] The concerns over massive collection of data are naturally extending to analytic tools applied to data. Data mining, with its promise to efficiently discover valuable, non obvious information from large databases, is particularly vulnerable to misuse [CM96] The98] Off98] ECB99] A fruitful ....
....assume that appropriate access controls and security procedures are in place and effective in preventing unauthorized access to the system. Other relevant work includes efforts to create tools and standards that provide platform for implementing a system such as ours (e.g. Wor] Ben99] GWB97] Cra99b] AC99] LM99] LEW99] Paper Organization We discuss privacy preserving methods in Section 2. We also introduce a quantitative measure to evaluate the amount of privacy offered by a method and evaluate the proposed methods against this measure. In Section 3, we present our reconstruction ....
Lorrie Faith Cranor, editor. Special Issue on Internet Privacy. Comm. ACM, 42(2), Feb. 1999.
On k-Anonymity and the Curse of Dimensionality - Charu Aggarwal Ibm (2005) (Correct)
No context found.
L. F. Cranor (Ed.) Special Issue on Internet Privacy. Communications of the ACM, 42(2), February 1999.
Privacy-Preserving Classification of Customer Data without.. - Yang, Zhong, Wright (2005) (Correct)
No context found.
L. Cranor, editor. Comm. ACM 42(2), Special Issue on Internet Privacy, 1999.
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