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
收藏
页码：99 / 110
页数：12
相关论文
共 50 条
  • [31] Steganalysis and payload estimation of embedding in pixel differences using neural networks
    Sabeti, Vajiheh
    Samavi, Shadrokh
    Mahdavi, Mojtaba
    Shirani, Shahram
    PATTERN RECOGNITION, 2010, 43 (01) : 405 - 415
  • [32] Recurrent Convolutional Neural Networks for AMR Steganalysis Based on Pulse Position
    Gong, Chen
    Yi, Xiaowei
    Zhao, Xianfeng
    Ma, Yi
    IH&MMSEC '19: PROCEEDINGS OF THE ACM WORKSHOP ON INFORMATION HIDING AND MULTIMEDIA SECURITY, 2019, : 2 - 13
  • [33] STEG-XAI: explainable steganalysis in images using neural networks
    Eugenia Kuchumova
    Sergio Mauricio Martínez-Monterrubio
    Juan A. Recio-Garcia
    Multimedia Tools and Applications, 2024, 83 : 50601 - 50618
  • [34] Modelling the soundscape quality of urban waterfronts by artificial neural networks
    Romero, Virginia Puyana
    Maffei, Luigi
    Brambilla, Giovanni
    Ciaburro, Giuseppe
    APPLIED ACOUSTICS, 2016, 111 : 121 - 128
  • [35] Modelling the Torque with Artificial Neural Networks on a Tunnel Boring Machine
    Paulo Cachim
    Adam Bezuijen
    KSCE Journal of Civil Engineering, 2019, 23 : 4529 - 4537
  • [36] Use of artificial neural networks for retention modelling in ion chromatography
    Srecnik, G
    Debeljak, Z
    Cerjan-Stefanovic, S
    Bolanca, T
    Novic, M
    Lazaric, K
    Gumhalter-Lulic, Z
    CROATICA CHEMICA ACTA, 2002, 75 (03) : 713 - 725
  • [37] Bayesian modelling of nonlinear Poisson regression with artificial neural networks
    Rodrigo, Hansapani
    Tsokos, Chris
    JOURNAL OF APPLIED STATISTICS, 2020, 47 (05) : 757 - 774
  • [38] Artificial neural networks modelling the prednisolone nanoprecipitation in microfluidic reactors
    Ali, Hany S. M.
    Blagden, Nicholas
    York, Peter
    Amani, Amir
    Brook, Toni
    EUROPEAN JOURNAL OF PHARMACEUTICAL SCIENCES, 2009, 37 (3-4) : 514 - 522
  • [39] Modelling Acetification with Artificial Neural Networks and Comparison with Alternative Procedures
    Jimenez-Hornero, Jorge E.
    Santos-Duenas, Ines Maria
    Garcia-Garcia, Isidoro
    PROCESSES, 2020, 8 (07)
  • [40] Artificial Neural Networks for Modelling the Degradation of Emerging Contaminants Process
    Dolores M. E. Álvarez
    María V. Gerbaldo
    Mario R. Modesti
    Silvia N. Mendieta
    Mónica E. Crivello
    Topics in Catalysis, 2022, 65 : 1440 - 1446
12345