• DocumentCode
    1877564
  • Title

    Rapid detection of stego images based on identifiable features

  • Author

    Weiwei Pang ; Xiangyang Luo ; Jie Ren ; Chunfang Yang ; Fenlin Liu

  • Author_Institution
    State Key Lab. of Math. Eng. & Adv. Comput., Zhengzhou, China
  • fYear
    2015
  • fDate
    1-3 July 2015
  • Firstpage
    472
  • Lastpage
    477
  • Abstract
    An increasing number of images in the Internet brings forward a higher requirement on the speed of steganalysis. For the problem of real-time detection of stego images, a method of images steganalysis rapidly based on identifiable features is proposed, where the identifiable features are specific character sequences left in stego images by steganography tools. According to finding whether an image contains these features can judge reliably the image is stego or cover. Meanwhile, for multiple identifiable features appearing on the same location of an image, an algorithm of identifiable features recognized based on AC (Aho-Corasick) multi-features matching algorithm is proposed, which can improve the detection speed. Experiment shows that the steganalysis method proposed can achieve a perfect detection precision, and the detection speed can be improved significantly comparing with traditional methods (matching bytes one by one).
  • Keywords
    feature extraction; image matching; image sequences; steganography; Aho-Corasick multifeatures matching; Internet; character sequences; detection speed; images steganalysis; multiple identifiable features; perfect detection precision; rapid detection; real-time detection; steganography tools; stego images; Algorithm design and analysis; Detection algorithms; Feature extraction; Head; Image resolution; Magnetic heads; Reliability; AC algorithm; Identifiable features; Steganalysis; Steganography tools; Stego image detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Communication Technology (ICACT), 2015 17th International Conference on
  • Conference_Location
    Seoul
  • Print_ISBN
    978-8-9968-6504-9
  • Type

    conf

  • DOI
    10.1109/ICACT.2015.7224840
  • Filename
    7224840