A recent version of the “Vawtrak” malware used steganography to hide the addresses of the command and control channels in favicons: small images automatically downloaded by the web browser. Since almost all research in steganalysis focuses on natural images, we study how well these methods can detect secret messages in favicons. The study is performed on a large corpus of favicons downloaded fr...

In this paper we provide a new digital video steganalysis algorithm. When frames of the cover video are embedded with secret messages, both number of connected component and number of holes will change dramatically, thus Euler number of the stego-frame will has pulsing increase. This proposed steganalysis algorithm is applied to stego-video, estimating steganographic algorithm for frames chosen...

This paper discusses a new heavy tailed distribution based data hiding into discrete cosine transform (DCT) coefficients of image, which provides statistical security as well as robustness against steganalysis attacks. Unlike other data hiding algorithms, the proposed technique does not introduce much effect in the stegoimage’s DCT coefficient probability plots, thus making the presence of hidd...

This paper presents a novel steganalysis scheme with highdimensional feature vectors derived from co-occurrence matrix in either spatial domain or JPEG coefficient domain, which is sensitive to data embedding process. The class-wise non-principal components analysis (CNPCA) is proposed to solve the problem of the classification in the high-dimensional feature vector space. The experimental resu...

This paper proposed a new steganalysis method against least significant bit (LSB) matching for images with high noise component which is considered more difficult for steganalysis than images with low noise component. First we calculate the sum of curvature of images histogram as discriminative feature which will reduce after LSB matching. Then, the calibration mechanism is introduced to reduce...

There are two primary challenges to monitoring the Web for steganographic media: finding suspect media and examining those found. The challenge that has received a great deal of attention is the second of these, the steganalysis problem. The other challenge, and one that has received much less attention, is the search problem. How does the steganalyzer get the suspect media in the first place? ...