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Privacy Preserving Optimized Rules Mining from Decision Tables and Decision Trees


Affiliations
1 Department of Computer Science, Faculty of Computing & I.T, King Abdulaziz University, Jeddah 21589, Saudi Arabia
 

With the swelling amount of data mining projects and information sharing, preserving privacy is a challenging issue which needs higher priority to guarantee security. This paper is an extension of Qureshi et al. (2010) with the addition of security features to the existing classification rules to preserve privacy. Experimental results show secure, accurate, sanitized and optimized rules which we achieve by using the concept of genetic algorithm (GA).

Keywords

Genetic Algorithm, Decision Tree, Decision Table, Knowledge Base, Classification Rules
User

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  • Privacy Preserving Optimized Rules Mining from Decision Tables and Decision Trees

Abstract Views: 418  |  PDF Views: 100

Authors

Ahmed Saeed Alzahrani
Department of Computer Science, Faculty of Computing & I.T, King Abdulaziz University, Jeddah 21589, Saudi Arabia
Muhammad Shuaib Qureshi
Department of Computer Science, Faculty of Computing & I.T, King Abdulaziz University, Jeddah 21589, Saudi Arabia

Abstract


With the swelling amount of data mining projects and information sharing, preserving privacy is a challenging issue which needs higher priority to guarantee security. This paper is an extension of Qureshi et al. (2010) with the addition of security features to the existing classification rules to preserve privacy. Experimental results show secure, accurate, sanitized and optimized rules which we achieve by using the concept of genetic algorithm (GA).

Keywords


Genetic Algorithm, Decision Tree, Decision Table, Knowledge Base, Classification Rules

References





DOI: https://doi.org/10.17485/ijst%2F2012%2Fv5i6%2F30471