Maintaining Data Privacy in Association Rule Mining

By Shariq Rizvi, Jayant R. Haritsa. 2002

572 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Sociology and Political Science

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

In Sociology and Political Science

Citations in the corpus

Privacy-Preserving Multivariate Statistical Analysis: Linear Regression and Classification (2004, methodology): “In general, there are two different approaches: one is to use data distortion approach, in which data are disguised by the added noises [1, 2, 13, 14, 22, 23].”
A framework for high-accuracy privacy-preserving mining (2004, methodology): “New randomization operators for maintaining data privacy for boolean data were presented and analyzed in [10, 14].”
Privacy-preserving distributed mining of association rules on horizontally partitioned data (2004, methodology): “More recently, the data distortion approach has been applie d to boolean association rules [6], [7].”
Deriving private information from randomized data (2005, methodology): “In the randomization approach, random noises are added to the original data, and only the disguised data are shared [2, 1, 21, 9, 7].”
Privacy Preserving Data Mining Research: Current Status and Key Issues (2007, unknown): “Data hiding [3] [4] [5] [6] [17] [18] [20] [29] [31] [2] [7] [8] [9] 10] [11] [23] [24] [25] [27] [30] [33] Rule hiding [14] [15] [16] [19] [27] [21] [22] None”
A General Survey of Privacy-Preserving Data Mining Models and Algorithms (2008, background): “This value is less than 1, since X can be localized to an interval of length less than one for many values of Z.”
On the privacy preserving properties of random data perturbation techniques (2003, background): “Evfimievski et al. [5] [4] and Rizvi [15] have also considered the approach in [2] in the context of association rule mining and suggest techniques for limiting privacy breaches.”
The applicability of the perturbation based privacy preserving data mining for real-world data (2008, methodology): “The perturbation approach has been also applied to Boolean association rules [10,11].”
Privacy preserving mining of association rules (2002, background): “At the same time, independently from our work, there was a paper [28] that considered another algorithm for randomizing transactions for privacy preserving mining of association rules.”
Mining interesting knowledge from weblogs: a survey (2005, methodology): “This approach was first presented in [108,109] with a specific focus on decision tree techniques; later [110,111] extended the focus to Association rules.”
Random projection-based multiplicative data perturbation for privacy preserving distributed data mining (2006, background): “Evfimievski et al. [10], [11] and Rizvi [ 12 ] considered the same approach in the context of association rule mining and suggested techniques for limiting privacy breaches.”
A Condensation Approach to Privacy Preserving Data Mining (2004, methodology): “For example, the work in [1] develops a new distribution based data mining algorithm for the classification problem, whereas the techniques in [9], and [16] develop methods for privacy preserving association rule mining.”
Limiting privacy breaches in privacy preserving data mining (2003, background): “This will be do ne for one important special case, previously discussed in [9, 17]: randomization of itemsets in association rule mining.”
Mining Association Rules under Privacy Constraints (2008, methodology): “In MASK [34], a simple probabilistic distortion of user data, employing random numbers generated from a pre-defined distribution function, was proposed and evaluated in the context of sparse boolean databases, such as those found in “market-baskets”.”
State-of-the-art in privacy preserving data mining (2004, background): “The work presented in [ 20 ] and [13] deal with binary and categorical data in the context of association rule mining.”