Image Steganography Approaches and Their Detection Strategies: A Survey

被引:0
|
作者
Kombrink, Meike helena [1 ,2 ]
Geradts, Zeno Jean Marius Hubert [1 ,2 ]
Hubert, Marius [2 ]
机构
[1] Netherlands Forens Inst, Digital & Biometr Traces, The Hague, Netherlands
[2] Univ Amsterdam, Informat Inst, Fac Sci, Amsterdam, Netherlands
基金
欧盟地平线“2020”;
关键词
CCS Concepts; Security and privacy -> Information-theoretic techniques; Pseudonymity; anonymity and untraceability; Information flow control; LEAST-SIGNIFICANT-BIT; PARTICLE SWARM OPTIMIZATION; DATA HIDING SCHEME; DIGITAL IMAGES; MODIFICATION DIRECTIONS; ADAPTIVE STEGANOGRAPHY; LEARNING FRAMEWORK; JPEG STEGANALYSIS; LSB STEGANOGRAPHY; EMBEDDING METHOD;
D O I
10.1145/3694965
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Steganography is the art and science of hidden (or covered) communication. In digital steganography, the bits of image, video, audio and text files are tweaked to represent the information to hide. This article covers the current methods for hiding information in images, alongside steganalysis methods that aim to detect the presence of steganography. By reviewing 456 references, this article discusses the different approaches that can be taken toward steganography and its much less widely studied counterpart. Currently in research older steganography approaches are more widely used than newer methods even though these show greater potential. New methods do have flaws; therefore, more research is needed to make these practically applicable. For steganalysis one of the greatest challenges is the generalisability. Often one scheme can detect the presence of one specific hiding method. More research is needed to combine current schemes and/or create new generalisable schemes. To allow readers to compare results between different papers in our work, performance indications of all steganalysis methods are outlined and a comparison of performance is included. This comparison is given using 'topological sorting' graphs, which compares detection results from all papers (as stated in the papers themselves) on different steganographic schemes.
引用
收藏
页数:40
相关论文
共 50 条
  • [31] Image steganography based on Kirsch edge detection
    Ghosal, Sudipta Kumar
    Chatterjee, Agneet
    Sarkar, Ram
    MULTIMEDIA SYSTEMS, 2021, 27 (01) : 73 - 87
  • [32] A Survey on Cloud Data Security using Image Steganography
    Albalawi, Afrah
    Hamza, Nermin
    INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2020, 11 (01) : 645 - 649
  • [33] Current status and key issues in image steganography: A survey
    Subhedar, Mansi S.
    Mankar, Vijay H.
    COMPUTER SCIENCE REVIEW, 2014, 13-14 (0C) : 95 - 113
  • [34] Detection of Hidden Encrypted URL in Image Steganography
    Aljamea, Moudhi
    Athar, Tanver
    Iliopoulos, Costas S.
    Samiruzzaman, M.
    NINTH INTERNATIONAL CONFERENCES ON PERVASIVE PATTERNS AND APPLICATIONS (PATTERNS 2017), 2017, : 3 - 8
  • [35] A Literature Survey on various Image Encryption & Steganography Techniques
    Dahiya, Madhu
    Kumar, Raman
    2018 FIRST INTERNATIONAL CONFERENCE ON SECURE CYBER COMPUTING AND COMMUNICATIONS (ICSCCC 2018), 2018, : 310 - 314
  • [36] Image forgery detection: a survey of recent deep-learning approaches
    Zanardelli, Marcello
    Guerrini, Fabrizio
    Leonardi, Riccardo
    Adami, Nicola
    MULTIMEDIA TOOLS AND APPLICATIONS, 2023, 82 (12) : 17521 - 17566
  • [37] Image forgery detection: a survey of recent deep-learning approaches
    Marcello Zanardelli
    Fabrizio Guerrini
    Riccardo Leonardi
    Nicola Adami
    Multimedia Tools and Applications, 2023, 82 : 17521 - 17566
  • [38] A Survey of Image Dehazing Approaches
    Chengtao, C.
    Qiuyu, Z.
    Yanhua, L.
    2015 27TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC), 2015, : 3964 - 3969
  • [39] Comprehensive survey of 3D image steganography techniques
    Girdhar, Ashish
    Kumar, Vijay
    IET IMAGE PROCESSING, 2018, 12 (01) : 1 - 10
  • [40] A Survey on Deep Convolutional Neural Networks for Image Steganography and Steganalysis
    Hussain, Israr
    Zeng, Jishen
    Xinhong
    Tan, Shunquan
    KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS, 2020, 14 (03): : 1228 - 1248