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A data modification technique in PPDM based on ant colony optimization approach
Ansari M.Z.H.1; Asghar S.2; Zhuang Y.3; Fong S.3
2015
Conference Name6th International Conference on Applications of Digital Information and Web
Source PublicationFrontiers in Artificial Intelligence and Applications
Volume275
Pages139-149
Conference DateFEB 12, 2015
Conference PlaceUniv Macau, Macao, PEOPLES R CHINA
PublisherIOS PRESS, NIEUWE HEMWEG 6B, 1013 BG AMSTERDAM, NETHERLANDS
Abstract

Data collection is being used in all fields nowadays. This data collection of data creates a dataset. Association rule mining is one of the data mining techniques used to extract hidden knowledge within the dataset. These rules are very useful for the organizations but on the other hand, these rules also generate sensitive or confidential information and patterns. Resolving the problem of hiding the sensitive or confidential information with the sensitivity patterns, Privacy preserving data mining (PPDM) is introduced. Privacy preserving data mining is used to hide sensitive and confidential information and patterns, and also preserves the knowledge of the dataset. Various techniques are used to hide such confidential and sensitive information, but they all produce lost rules, ghost rules and hidden failure ratio. In current research work, we propose an algorithm which is based on ant colony optimization (ACO) technique. This proposed methodology is used to triumph over the problem of lost rules, ghost rules and hidden failure ratio. Fuzzy sets are used as the fitness function of ACO. The technique minimizes the problem of lost rule, ghost rule and hidden failure ratio in a great manner. Further-more, this technique is used in all types of areas for hiding sensitive information with sensitive patterns.

KeywordAco Ant Colony Optimization Ppdm Privacy Preserving Data Mining
DOIhttps://doi.org/10.3233/978-1-61499-503-6-139
URLView the original
Indexed BySCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Information Systems ; Computer Science, Theory & Methods
WOS IDWOS:000360235300012
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Cited Times [WOS]:1   [WOS Record]     [Related Records in WOS]
Document TypeConference paper
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Affiliation1.UIIT Department Pir Mehr Ali Shah Rawalpindi, Pakistam
2.COMSATS Institute of Information Technology, Islamabad, Pakistam
3.Department of Computer and Information Science, University of Macau, Taipa, Macau SAR
Recommended Citation
GB/T 7714
Ansari M.Z.H.,Asghar S.,Zhuang Y.,et al. A data modification technique in PPDM based on ant colony optimization approach[C]:IOS PRESS, NIEUWE HEMWEG 6B, 1013 BG AMSTERDAM, NETHERLANDS,2015:139-149.
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