Digital Watermarking Using Artificial Intelligence: Concept, Techniques, and Future Trends

被引:0
|
作者
Dandooh, Azza [1 ]
El-Fishawy, Adel S. [2 ]
Hemdan, Ezz El-Din [3 ,4 ]
机构
[1] Egyptian Acad Engn & Adv Technol EAE&AT, Dept Elect Engn, Cairo, Egypt
[2] Menoufia Univ, Fac Elect Engn, Dept Elect & Commun, Menoufia, Egypt
[3] Menoufia Univ, Fac Elect Engn, Dept Comp Sci & Engn, Menoufia, Egypt
[4] Prince Sultan Univ, Struct & Mat Res Lab, Riyadh, Saudi Arabia
来源
SECURITY AND PRIVACY | 2025年 / 8卷 / 01期
关键词
artificial intelligence; digital watermarking; machine learning and deep learning; SCHEME; ROBUST;
D O I
10.1002/spy2.502
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
One of the most widely used tools for information security is digital watermarking. Multimedia content, including text, audio, video, and images, frequently uses it. Utilizing watermarking requires different goals. These goals encompass copyright authentication as well as protection. It might be necessary for the watermark to be strong or fragile. Applications requiring copyright authentication must include a fragile watermark. However, copyright protection necessitates a strong watermark. For resolving a variety of intelligence-related issues, machine learning (ML) and deep learning (DL) are solid options. Although it works well for watermarking, it is less effective at more common tasks like regression, classification, and prediction. A thorough analysis of watermarking with popular technologies like artificial intelligence (AI), DL, and ML is presented in this article. A summary of watermarking, background information, and the most interesting applications are also covered.
引用
收藏
页数:15
相关论文
共 50 条
  • [41] Artificial Intelligence in Public Health: Current Trends and Future Possibilities
    Giansanti, Daniele
    INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2022, 19 (19)
  • [42] Artificial intelligence in interventional radiology: Current concepts and future trends
    Lesaunier, Armelle
    Khlaut, Julien
    Dancette, Corentin
    Tselikas, Lambros
    Bonnet, Baptiste
    Boeken, Tom
    DIAGNOSTIC AND INTERVENTIONAL IMAGING, 2025, 106 (01) : 5 - 10
  • [43] Periodontitis diagnosis: A review of current and future trends in artificial intelligence
    Jundaeng, Jarupat
    Chamchong, Rapeeporn
    Nithikathkul, Choosak
    TECHNOLOGY AND HEALTH CARE, 2025, 33 (01) : 473 - 484
  • [44] Artificial intelligence: a survey on evolution, models, applications and future trends
    Lu, Yang
    JOURNAL OF MANAGEMENT ANALYTICS, 2019, 6 (01) : 1 - 29
  • [45] ARTIFICIAL INTELLIGENCE APPLICATIONS IN THE ATMOSPHERIC ENVIRONMENT: STATUS AND FUTURE TRENDS
    Karatzas, Kostas D.
    ENVIRONMENTAL ENGINEERING AND MANAGEMENT JOURNAL, 2010, 9 (02): : 171 - 180
  • [46] DIGITAL INTELLIGENCE - NEW CONCEPT IN CONTEXT OF FUTURE OF SCHOOL EDUCATION
    Dostal, Jiri
    Wang, Xiaojun
    Steingartner, William
    Nuangchalerm, Prasart
    10TH INTERNATIONAL CONFERENCE OF EDUCATION, RESEARCH AND INNOVATION (ICERI2017), 2017, : 3706 - 3712
  • [47] Digital watermarking method using compression concept and coefficient difference
    Hu, M-C
    Lou, D-C
    Tso, H-K
    IMAGING SCIENCE JOURNAL, 2007, 55 (03): : 155 - 163
  • [48] Digital Watermarking Techniques and Their Analysis
    Garg, Payal
    Jain, Ajit Kumar
    SMART SYSTEMS: INNOVATIONS IN COMPUTING (SSIC 2021), 2022, 235 : 41 - 54
  • [49] Survey on digital watermarking techniques
    Shukla, Deepti
    Tiwari, Nirupama
    International Journal of Signal Processing, Image Processing and Pattern Recognition, 2015, 8 (09) : 121 - 126
  • [50] Comparison of Digital Watermarking Techniques
    Aparna, J. R.
    Ayyappan, Sonal
    2014 INTERNATIONAL CONFERENCE FOR CONVERGENCE OF TECHNOLOGY (I2CT), 2014,