DocumentCode
3391200
Title
Hiding association rules based on relative-non-sensitive frequent itemsets
Author
Li, Xueming ; Liu, Zhijun ; Zuo, Chuan
Author_Institution
Chongqing Inst. of Meteorol. Sci., Chongqing, China
fYear
2009
fDate
15-17 June 2009
Firstpage
384
Lastpage
389
Abstract
Association rules hiding algorithms often sanitize transactional databases for protecting sensitive information. Data modification is one of the most important sanitation approaches. However, the exist modification methods either focus on hiding sensitive rules only, or take measures to reduce the impact on non-sensitive rules from the whole database while hiding sensitive rules. In this paper, we propose a new algorithm which hides sensitive rules from the side of non-sensitive rules. It classifies the sensitive transactions by their degree of conflict. For the special group of transactions, a victim-item must satisfy: 1, in the sensitive rules; 2, not in the non-sensitive rules. Our algorithm selects different victim-items in different transactions that contain the same rule, which makes sure that removing the victim-items in the special group of transactions has no influence to non-sensitive rules. The experimental results show that our algorithm for sanitizing transactional database can achieve better results compared with others algorithms such as Naiumlve, MinFIA, MaxFIA and IGA. In particular, our algorithm has the least impact on non-sensitive rules.
Keywords
data mining; database management systems; security of data; data modification; hiding association rules; information protection; relative nonsensitive frequent itemsets; sanitation approaches; transactional database; victim-item; Adaptation model; Association rules; Atmospheric modeling; Bridges; Computer science; Context modeling; Itemsets; Knowledge acquisition; Knowledge representation; Proposals; Association rules; Frequent itemsets; Privacy preserving data mining;
fLanguage
English
Publisher
ieee
Conference_Titel
Cognitive Informatics, 2009. ICCI '09. 8th IEEE International Conference on
Conference_Location
Kowloon, Hong Kong
Print_ISBN
978-1-4244-4642-1
Type
conf
DOI
10.1109/COGINF.2009.5250708
Filename
5250708
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