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Publishing Sensitive Transactions for Itemset Utility
2008
2008 Eighth IEEE International Conference on Data Mining
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We consider the problem of publishing sensitive transaction data with privacy preservation. High dimensionality of transaction data poses unique challenges on data privacy and data utility. ...
On one hand, re-identification attacks tend to use a subset of items that infrequently occur in transactions, called moles. ...
Data Utility Typically transaction data are published for data mining applications where sets of items that co-occur frequently, also called frequent itemsets in [7] , represent associations between items ...
doi:10.1109/icdm.2008.98
dblp:conf/icdm/XuFWFP08
fatcat:r2oxandc7va2vjglvkclpq4lii
Hiding Sensitive High Utility and Frequent Itemsets Based on Constrained Intersection Lattice
2022
Cybernetics and Information Technologies
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Its goal is to remove sensitive high utility and frequent itemsets from a database before sharing it for data mining purposes while minimizing the side effects. ...
Hiding high utility and frequent itemset is the method used to preserve sensitive knowledge from being revealed by pattern mining process. ...
In order to select the method for hiding sensitive high utility and frequent itemset, Liu, Xu and Lv [12] have defined a maximal utility border and a minimal utility border notions for sensitive itemset ...
doi:10.2478/cait-2022-0001
fatcat:is3sfsqmmfan3i5b4e5z6jfnjy
On differentially private frequent itemset mining
2012
Proceedings of the VLDB Endowment
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Related work has proposed differentially private algorithms for the top-k itemset mining problem ("find the k most frequent itemsets".) ...
We consider differentially private frequent itemset mining. We begin by exploring the theoretical difficulty of simultaneously providing good utility and good privacy in this task. ...
To utilize the geometric mechanism, we need to compute the sensitivity of q. ...
doi:10.14778/2428536.2428539
pmid:24039383
pmcid:PMC3771517
fatcat:aly5rcjiybglvcm52li5pfs3he
Hiding co-occurring frequent itemsets
2009
Proceedings of the 2009 EDBT/ICDT Workshops on - EDBT/ICDT '09
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Knowledge hiding, hiding rules/patterns that are inferable from published data and attributed sensitive, is extensively studied in the literature in the context of frequent itemsets and association rules ...
What is different from the classical frequent hiding is the new sensitivity definition: an itemset set is sensitive if its itemsets appear altogether within the frequent itemset mining results. ...
transaction list for every sensitive itemset and computing the number of sensitive transactions to be sanitized, (4) sorting the sensitive transactions by size, (5) sanitizing the transaction by removing ...
doi:10.1145/1698790.1698810
dblp:conf/edbtw/Abul09
fatcat:vqjoyxe73bcc7gy3mxoq4ywcwq
High utility-itemset mining and privacy-preserving utility mining
2016
Perspectives in Science
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In this paper, we focus on the issues of HUIM and privacy-preserving utility mining (PPUM), and present two evolutionary algorithms to respectively mine HUIs and hide the sensitive high-utility itemsets ...
Extensive experiments showed that the two proposed models for the applications of HUIM and PPUM can not only generate the high quality profitable itemsets according to the user-specified minimum utility ...
For the purpose of PPUM in this paper, the sensitive high-utility itemsets are required to be hidden through transaction deletion in the sanitization process. ...
doi:10.1016/j.pisc.2015.11.013
fatcat:t5y7zxkhkzc7rpdopq7gbs4lwi
Frequent Itemsets Mining With Differential Privacy Over Large-Scale Data
2018
IEEE Access
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Current solutions for this problem cannot well balance efficiency, privacy, and data utility over large-scale data. ...
Based on the ideas of sampling and transaction truncation using length constraints, our algorithm reduces the computation intensity, reduces mining sensitivity, and thus improves data utility given a fixed ...
For the above two utility measures, the larger F-Score is, the closer the frequent itemsets to the real itemsets; it indicates that the utility of the algorithm is higher. ...
doi:10.1109/access.2018.2839752
fatcat:zh7v5mexkrgvlj3it5jyxl6sry
Transactional Data Anonymization for Privacy and Information Preservation via Disassociation and Local Suppression
2022
Symmetry
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Disassociation is a popular method for transactional data anonymization against re-identification attacks in privacy-preserving data publishing. ...
datasets, thus decreasing the data quality of the published transactions. ...
The itemsets to be anonymized and sensitive items to be protected are specified by data publishers. ...
doi:10.3390/sym14030472
fatcat:yfqxmaztenczbpqslowkanpoga
Privacy preserving association rule hiding using border based approach
2021
Indonesian Journal of Electrical Engineering and Computer Science
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In this paper, we introduce a border-based algorithm for hiding sensitive association rules. ...
In the majority of the situations, data mining results contain sensitive information about individuals and publishing such data will violate individual secrecy. ...
[10] proposed SIF-IDF technique that utilizes TF-IDF measure to determine the similarity between transactions and sensitive itemsets. ...
doi:10.11591/ijeecs.v23.i2.pp1137-1145
fatcat:bqzyk7wztvbv5aygwlsqohgaqu
Privacy Preserving Utility Mining: A Survey
[article]
2018
arXiv
pre-print
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for PPUM. ...
However, analysis of these data with sensitive private information raises privacy concerns. ...
In some real-world applications, the sensitive high-utility patterns (i.e., itemsets, It has good performance on condense database, but has high overlap sensitive itemsets.
2010 FPUTT [17] Transaction ...
arXiv:1811.07389v1
fatcat:upooi44vzretxavpkp2lie735i
An Optimization based Modified Maximum Sensitive Item-Sets Conflict First Algorithm (MSICF) for Hiding Sensitive Item-Sets
2013
International Journal of Computer Applications
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The MMSICF algorithm computes the sensitive itemsets by utilizing the user defined utility threshold value. ...
In privacy preserving utility mining, some sensitive itemsets are hidden from the database according to certain privacy policies. ...
For example, } , { B A is a sensitive itemset ) 120 ( , having utility value 200 ) , ( B A u . ...
doi:10.5120/12479-8881
fatcat:hmmumjsbgrbzbmafrptno4orni
Association rule hiding using integer linear programming
2021
International Journal of Power Electronics and Drive Systems (IJPEDS)
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Hence, association rule hiding emerged as one of the powerful techniques for hiding sensitive knowledge that exists in data before it is published. ...
The solution of the integer linear program determines the transactions that need to be sanitized in order to conceal the sensitive rules while minimizing the impact of sanitization on the non-sensitive ...
[21] utilized ILP to formulate a CSP that determines the least number of transaction sanitizations in order to conceal sensitive itemsets. ...
doi:10.11591/ijece.v11i4.pp3451-3458
fatcat:onlp2lj375gsphdcgrzr32xx2m
Privacy Preserving Web Query Log Publishing: A Survey on Anonymization Techniques
[article]
2012
arXiv
pre-print
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Releasing Web query logs which contain valuable information for research or marketing, can breach the privacy of search engine users. ...
Therefore rendering query logs to limit linking a query to an individual while preserving the data usefulness for analysis, is an important research problem. ...
Itemset based utility [20] is another utility measure which captures frequent itemsets in transaction data. ...
arXiv:1211.2354v1
fatcat:5cqn62az5vfyvonn7wjmdwproy
An effective scheme for top-k frequent itemset mining under differential privacy conditions
2020
Science China Information Sciences
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To promote the utility of the release result, a potential solution evaluated in previously published studies was to decrease the dimension of long transactions in a differentially private manner before ...
An effective scheme for top-k frequent itemset mining under differential privacy conditions. ...
To promote the utility of the release result, a potential solution evaluated in previously published studies was to decrease the dimension of long transactions in a differentially private manner before ...
doi:10.1007/s11432-018-9849-y
fatcat:byhvt7vr3ff23nst2zrwbewvde
PrivBasis: Frequent Itemset Mining with Differential Privacy
[article]
2012
arXiv
pre-print
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We introduce algorithms for privately constructing a basis set and then using it to find the most frequent itemsets. ...
In this paper, we study the problem of how to perform frequent itemset mining on transaction databases while satisfying differential privacy. ...
Hence the sensitivity of publishing all bin counts for one basis is 1; and the sensitivity for publishing counts for all bases is w. In Algorithm 1, lines 2 to 11 compute these noisy bin frequencies. ...
arXiv:1208.0093v1
fatcat:2gvi5z4bhffojex7rjazczv4gi
PrivBasis
2012
Proceedings of the VLDB Endowment
Preserved Fulltext
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In this paper, we study the problem of how to perform frequent itemset mining on transaction databases while satisfying differential privacy. ...
We introduce algorithms for privately constructing a basis set and then using it to find the most frequent itemsets. ...
Hence the sensitivity of publishing all bin counts for one basis is 1; and the sensitivity for publishing counts for all bases is w. In Algorithm 1, lines 2 to 11 compute these noisy bin frequencies. ...
doi:10.14778/2350229.2350251
fatcat:jfhgyho54nc3vkgr2kmr3jqloa
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