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Detection of Encrypted Data Based on Support Vector Data Description

Authors :
Zhisong Pan
Juan Meng
Yuhuan Zhou
Source :
CBD
Publication Year :
2013
Publisher :
IEEE, 2013.

Abstract

Data encryption has been widely used. It is important to detect encrypted data. We present a method for detection of encrypted data based on the Support Vector Data Description (SVDD) algorithm. The SVDD is a single class, non-parametric approach for modeling the support of a distribution. We apply the SVDD techniques for detection of encrypted data. Experimental results show that the SVDD can be adopted as an effective tool for detection of encrypted data.

Details

Database :
OpenAIRE
Journal :
2013 International Conference on Advanced Cloud and Big Data
Accession number :
edsair.doi...........64503058edd800715feaf6e1f9679581
Full Text :
https://doi.org/10.1109/cbd.2013.17