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3D STEGANALYSIS USING THE EXTENDED LOCAL FEATURE SET

Citation Author(s):
Daofu Gong, Fenlin Liu
Submitted by:
Adrian Bors
Last updated:
4 October 2018 - 5:27pm
Document Type:
Poster
Document Year:
2018
Event:
Presenters:
Dr. Adrian Bos
Paper Code:
MP.P9.4
 

3D steganalysis aims to find the changes embedded through steganographic or information hiding algorithms into 3D models. This research study proposes to use new 3D features, such as the edge vectors, represented in both Cartesian and Laplacian coordinate systems, together with other steganalytic features, for improving the results of 3D steganalysers. In this way the local feature vector used by the steganalyzer is extended to 124 dimensions. We test the performance of the extended local feature set, and compare it to four other steganalytic features, when detecting the stego-objects watermarked by six information hiding algorithms.

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