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
  • [1] Blind Image Steganalysis using Neural Networks and Wrapper Feature Selection
    Chhikara, Rita
    Kumari, Meena
    2017 IEEE INTERNATIONAL CONFERENCE ON COMPUTING, COMMUNICATION AND AUTOMATION (ICCCA), 2017, : 1065 - 1069
  • [2] Microbial growth modelling with artificial neural networks
    Jeyamkondan, S
    Jayas, DS
    Holley, RA
    INTERNATIONAL JOURNAL OF FOOD MICROBIOLOGY, 2001, 64 (03) : 343 - 354
  • [3] Industrial reactor modelling with artificial neural networks
    Montague, GA
    Gent, C
    Morris, AJ
    Buttress, J
    TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL, 1996, 18 (03) : 118 - 124
  • [4] Hydrological modelling using artificial neural networks
    Dawson, CW
    Wilby, RL
    PROGRESS IN PHYSICAL GEOGRAPHY-EARTH AND ENVIRONMENT, 2001, 25 (01): : 80 - 108
  • [5] Modelling TBM performance with artificial neural networks
    Benardos, AG
    Kaliampakos, DC
    TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY, 2004, 19 (06) : 597 - 605
  • [6] Feature learning for steganalysis using convolutional neural networks
    Qian, Yinlong
    Dong, Jing
    Wang, Wei
    Tan, Tieniu
    MULTIMEDIA TOOLS AND APPLICATIONS, 2018, 77 (15) : 19633 - 19657
  • [7] Architectural Modifications to Enhance Steganalysis with Convolutional Neural Networks
    Martyniak, Remigiusz
    Czaplewski, Bartosz
    COMPUTATIONAL SCIENCE, ICCS 2024, PT II, 2024, 14833 : 50 - 67
  • [8] Artificial Neural Networks in numerical modelling of composites
    Lefik, M.
    Boso, D. P.
    Schrefler, B. A.
    COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 2009, 198 (21-26) : 1785 - 1804
  • [9] Reference Channels for Steganalysis of Images with Convolutional Neural Networks
    Chen, Mo
    Boroumand, Mehdi
    Fridrich, Jessica
    IH&MMSEC '19: PROCEEDINGS OF THE ACM WORKSHOP ON INFORMATION HIDING AND MULTIMEDIA SECURITY, 2019, : 188 - 197
  • [10] Feature learning for steganalysis using convolutional neural networks
    Yinlong Qian
    Jing Dong
    Wei Wang
    Tieniu Tan
    Multimedia Tools and Applications, 2018, 77 : 19633 - 19657