SIMULATION MODELLING OF ARTIFICIAL NEURAL NETWORKS FOR THE PURPOSES OF STEGANALYSIS

被引：0

作者：

Ivanova, Yoana ^{[1
]}

机构：

[1] New Bulgarian Univ, Dept Telecommun, Sofia, Bulgaria

来源：

INTERNATIONAL JOURNAL ON INFORMATION TECHNOLOGIES AND SECURITY | 2022年 / 14卷 / 02期

关键词：

steganography; steganalysis; histogram equalization; LSB; Virtual Steganographic Laboratory; Artificial Neural Networks;

D O I：

暂无

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 paper is considered to be a continuation of previous publications devoted to applications of simulation modelling in cybersecurity and in particular the use of Artificial Neural Networks (ANNs) with Backpropagation of Error for digital recognition (IJITS, No4, 2021). It aims to present advanced steganographic methods that are applicable for the purposes of steganalysis to ensure the information protection. The empirical study and the experimental analysis made contribute to explaining various steganographic approaches that are applicable in security.

引用

页码：99 / 110

页数：12

共 13 条

[1]

[Anonymous], 2011, VIRTUAL STEGANOGRAPH

[2]

[Anonymous], 2020, HISTOGRAM EQUALIZATI

[3]

[Anonymous], 2019, STEGANALYSIS STEGANO

[4]

Bartel J., 2002, GIAC CERTIFICATIONS

[5]

Gupta R., 2014, International Journal of Computer Trends and Technology, V10, P21

[6]

Hsu CS, 2019, INT J INF TECHNOL SE, V11, P107

[7]

Johnson N.F., 2001, INFORM HIDING STEGAN, V1

[8]

Kashyap R., 2019, INT J ENG ADV TECHNO, V8, P788

[9]

Khaire S. S., 2010, INT J ENG SCI TECHNO, V2, P4862

[10]

Mustafaev AG, 2018, INT J INF TECHNOL SE, V10, P57

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