Blind steganalysis for digital images using support vector machine method
Menori M.H.a, Munir R.a
a School of Electrical Engineering and Informatics, Bandung Institute of Technology, Bandung, Indonesia
Abstract
© 2016 IEEE.Blind steganalysis is a method used to detect whether there is a hidden message in a media without having to know the steganography algorithm behind it. Digital image is converted into features using feature extraction algorithm subtractive pixel adjacency matrix. A model is built based on the resulting features using machine learning method support vector machine. The support vector machine method has different kernel configuration options, which are linear, polynomial, and Gaussian. The model that has been built then undergoes a testing to measure the accuracy performance in message detection and message length estimation. From the model testing, it is obtained that the accuracy in message detection shows good result while the accuracy in message length estimation does not. Highest accuracy is obtained with polynomial kernel.
Author keywords
Adjacency matrices,Blind steganalysis,Configuration options,Digital image,Feature extraction algorithms,Machine learning methods,Message length estimations,Support vector machine method
Indexed keywords
blind steganalysis,digital images,feature extraction,support vector machine