Title :
A Novel Anti-data Mining Technique Based On Hierarchical Anti-clustering (HAC)
Author :
Chen, Tung-Shou ; Chen, Jeanne ; Kao, Yuan-Hung ; Hsieh, Tsang-Chou
Author_Institution :
Grad. Sch. of Comput. Sci. & Inf. Technol., Nat. Taichung Inst. of Technol., Taichung
Abstract :
Data mining is a technique to search potential valuable information from databases. Preventing personal data and high security data therefore pose a difficult task to IT experts. In this paper, we propose a novel anti-data mining (ADM) database security scheme, that protect against data mining. The scheme makes use of hierarchical clustering where noise is added to change the cluster structure of data. The proposed hierarchical anti-clustering (HAC) scheme modifies the cluster structure of the original data. Experimented results show that data may be protected against during the HAC key can be used reverse the cluster structure to its original. At the meantime, HAC also designs the key value to restore correctly the protected database.
Keywords :
data mining; security of data; anti-data mining database security scheme; anti-data mining technique; hierarchical anti-clustering scheme; Association rules; Clustering algorithms; Companies; Data mining; Data security; Information security; Information technology; Protection; Spatial databases; Transaction databases; Anti-Clustering; Anti-Data Mining; Data Mining; Hierarchical Clustering; Noise data;
Conference_Titel :
Intelligent Systems Design and Applications, 2008. ISDA '08. Eighth International Conference on
Conference_Location :
Kaohsiung
Print_ISBN :
978-0-7695-3382-7
DOI :
10.1109/ISDA.2008.155