Steganalysis Method of Static JPEG Images Based on Artificial Immune System

被引：0

作者：

Shniperov, A. N. ^{[1
]}

Prokofieva, A. V. ^{[1
]}

机构：

[1] Siberian Fed Univ, Dept Appl Math & Comp Secur, Krasnoyarsk 660041, Russia

来源：

AUTOMATIC CONTROL AND COMPUTER SCIENCES | 2020年 / 54卷 / 05期

关键词：

Steganalysis; JPEG; binary classification; Haar wavelet-transform; Clonal selection; Negative selection;

D O I：

10.3103/S0146411620050077

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This work aims to develop the heuristic steganalysis method of static JPEG images, based on the usage of artificial immune systems that allows detecting the presence of hidden information in them with good results on image processing time. A formal description of the artificial immune system's primary nodes and an analysis of the obtained experimental results are presented. The proposed method allows detecting the presence of hidden information embedded by various popular steganography tools (like OutGuess, Steghide, and F5) in static JPEG images with sufficiently high accuracy.

引用

页码：423 / 431

页数：9

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