Improved Privacy Preserving decision tree Approach for Network Intrusion Detection
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International Journal of Computer & Organization Trends (IJCOT) | 
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| © 2016 by IJCOT Journal | ||
| Volume - 6 Issue - 1 |
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| Year of Publication : 2016 | ||
| Authors : S.Navya Sai, K.KishoreRaju | ||
| DOI : 10.14445/22492593/IJCOT-V30P301 |
Citation
S.Navya Sai, K.KishoreRaju"Improved Privacy Preserving decision tree Approach for Network Intrusion Detection", International Journal of Computer & organization Trends (IJCOT), V6(1):55-60 Jan - Feb 2016, ISSN:2249-2593, www.ijcotjournal.org. Published by Seventh Sense Research Group.
Abstract With the size of the data increases, privacy preserving plays a vital role in machine learning models. Privacy preserving becomes popular due to its privacy sensitive attributes for data analysis and decision making system.Machine learning has been used and applied in many areas including business development and internet of things. But, machine learning models occur serious problems due to its sensitive information and privacy violation. Privacy preserving data mining protects the sensitive information from disclosure without the permission of data providers. In this model, a novel privacy preserving data mining model was designed to protect the sensitive attributes in the KDD99 dataset.Experimental results show that proposed model has high true positive rate along with sensitive information compared to traditional models.
References
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Keywords
NID, P R I V ACY R E S E R VING.