A Review on the Recent Trends of Image Steganography for VANET Applications

被引:1
作者
Ansari, Arshiya S. [1 ]
机构
[1] Majmaah Univ, Coll Comp & Informat Sci, Dept Informat Technol, Al Majmaah 11952, Saudi Arabia
来源
CMC-COMPUTERS MATERIALS & CONTINUA | 2024年 / 78卷 / 03期
关键词
Steganography; image steganography; image steganography techniques; information exchange; data embedding and extracting; vehicular ad hoc network (VANET); transportation system; SPATIAL DOMAIN; ALGORITHM; LSB; STEGANALYSIS; SECURE; TRANSFORM;
D O I
10.32604/cmc.2024.045908
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Image steganography is a technique of concealing confidential information within an image without dramatically changing its outside look. Whereas vehicular ad hoc networks (VANETs), which enable vehicles to communicate with one another and with roadside infrastructure to enhance safety and traffic flow provide a range of value-added services, as they are an essential component of modern smart transportation systems. VANETs steganography has been suggested by many authors for secure, reliable message transfer between terminal/hope to terminal/hope and also to secure it from attack for privacy protection. This paper aims to determine whether using steganography is possible to improve data security and secrecy in VANET applications and to analyze effective steganography techniques for incorporating data into images while minimizing visual quality loss. According to simulations in literature and real-world studies, Image steganography proved to be an effective method for secure communication on VANETs, even in difficult network conditions. In this research, we also explore a variety of steganography approaches for vehicular ad-hoc network transportation systems like vector embedding, statistics, spatial domain (SD), transform domain (TD), distortion, masking, and filtering. This study possibly shall help researchers to improve vehicle networks' ability to communicate securely and lay the door for innovative steganography methods.
引用
收藏
页码:2865 / 2892
页数:28
相关论文
共 179 条
  • [91] Adversarial batch image steganography against CNN-based pooled steganalysis
    Li, Li
    Zhang, Weiming
    Qin, Chuan
    Chen, Kejiang
    Zhou, Wenbo
    Yu, Nenghai
    [J]. SIGNAL PROCESSING, 2021, 181
  • [92] Adaptive Payload Distribution in Multiple Images Steganography Based on Image Texture Features
    Liao, Xin
    Yin, Jiaojiao
    Chen, Mingliang
    Qin, Zheng
    [J]. IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING, 2022, 19 (02) : 897 - 911
  • [93] A New Payload Partition Strategy in Color Image Steganography
    Liao, Xin
    Yu, Yingbo
    Li, Bin
    Li, Zhongpeng
    Qin, Zheng
    [J]. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2020, 30 (03) : 685 - 696
  • [94] A digital data hiding scheme based on pixel-value differencing and side match method
    Liu, Hsing-Han
    Lin, Yuh-Chi
    Lee, Chia-Ming
    [J]. MULTIMEDIA TOOLS AND APPLICATIONS, 2019, 78 (09) : 12157 - 12181
  • [95] Recent Advances of Image Steganography With Generative Adversarial Networks
    Liu, Jia
    Ke, Yan
    Zhang, Zhuo
    Lei, Yu
    Li, Jun
    Zhang, Minqing
    Yang, Xiaoyuan
    [J]. IEEE ACCESS, 2020, 8 (60575-60597) : 60575 - 60597
  • [96] LSB steganographic payload location for JPEG-decompressed images
    Liu, Jiu-fen
    Tian, Yu-guo
    Han, Tao
    Yang, Chun-fang
    Liu, Wen-bin
    [J]. DIGITAL SIGNAL PROCESSING, 2015, 38 : 66 - 76
  • [97] Rob-GAN: Generator, Discriminator, and Adversarial Attacker
    Liu, Xuanqing
    Hsieh, Cho-Jui
    [J]. 2019 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2019), 2019, : 11226 - 11235
  • [98] A more secure steganography based on adaptive pixel-value differencing scheme
    Luo, Weiqi
    Huang, Fangjun
    Huang, Jiwu
    [J]. MULTIMEDIA TOOLS AND APPLICATIONS, 2011, 52 (2-3) : 407 - 430
  • [99] Edge Adaptive Image Steganography Based on LSB Matching Revisited
    Luo, Weiqi
    Huang, Fangjun
    Huang, Jiwu
    [J]. IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, 2010, 5 (02) : 201 - 214
  • [100] A creative approach to understanding the hidden information within the business data using Deep Learning
    Luo, Yuanfeng
    Yao, Chuantao
    Mo, Yue
    Xie, Baoji
    Yang, Guijun
    Gui, Huiyang
    [J]. INFORMATION PROCESSING & MANAGEMENT, 2021, 58 (05)