Coverless Video Steganography Based on Audio and Frame Features

• Published in: Security and communication networks 2022-04, Vol.2022, p.1-14
• Main Authors: Zhang, Chunhu, Tan, Yun, Qin, Jiaohua, Xiang, Xuyu
• Format: Article
• Language: English
• Subjects: Algorithms; Discrete Wavelet Transform; Feature extraction; Information retrieval; Neural networks; Receivers & amplifiers; Signal processing; Steganography; Video; Wavelet transforms
• ISSN: 1939-0114; 1939-0122
• DOI: 10.1155/2022/1154098

The coverless steganography based on video has become a research hot spot recently. However, the existing schemes usually hide secret information based on the single-frame feature of video and do not take advantage of other rich features. In this work, we propose a novel coverless steganography, which makes full use of the audio and frame image features of the video. First, three features are extracted to obtain hash bit sequences, which include DWT (discrete wavelet transform) coefficients and short-term energy of audio and the SIFT (scale-invariant feature transformation) feature of frame images. Then, we build a retrieval database according to the relationship between the generated bit sequences and three features of the corresponding videos. The sender divides the secret information into segments and sends the corresponding retrieval information and carrier videos to the receiver. The receiver can use the retrieval information to recover the secret information from the carrier videos correspondingly. The experimental results show that the proposed method can achieve larger capacity, less time cost, higher hiding success rate, and stronger robustness compared with the existing coverless steganography schemes based on the video.