Biblio

Steganography is the technique of hiding a confidential message in an ordinary message where the extraction of embedded information is done at its destination. Among the different carrier files formats; digital images are the most popular. This paper presents a Wavelet-based method for hiding secret information in digital images where skin areas are identified and used as a region of interest. The work presented here is an extension of a method published earlier by the authors that utilized a rule-based approach to detect skin regions. The proposed method, proposed embedding the secret data into the integer Wavelet coefficients of the approximation sub-band of the cover image. When compared to the original technique, experimental results showed a lower error percentage between skin maps detected before the embedding and during the extraction processes. This eventually increased the similarity between the original and the retrieved secret image.

Since the last few decades, several chaotic encryption techniques are reported by different researchers. Although the cryptanalysis of some techniques shows the feebler resistance of those algorithms against any weaker attackers. However, different hyper-chaotic based and DNA-coding based encrypting methods are introduced recently. Though, these methods are efficient against several attacks, but, increase complexity as well. On account of these drawbacks, we have proposed a novel technique of chaotic encryption of an image using the integer wavelet transform (IWT) and global bit scrambling (GBS). Here, the image is transformed and decomposed by IWT. Thereafter, a chaotic map is used in the encryption algorithm. A key-dependent bit scrambling (GBS) is introduced rather than pixel scrambling to make the encryption stronger. It enhances key dependency along with the increased resistance against intruder attacks. To check the fragility and dependability of the algorithm, a sufficient number of tests are done, which have given reassuring results. Some tests are done to check the similarity between the original and decrypted image to ensure the excellent outcome of the decryption algorithm. The outcomes of the proposed algorithm are compared with some recent works' outputs to demonstrate its eligibility.

Remote authentication via biometric features has received much attention recently, hence the security of biometric data is of great importance. Here a crypto-steganography method applied for the protection of biometric data is implemented. It include semantic segmentation, chaotic encryption, data hiding and fingerprint recognition to avoid the risk of spoofing attacks. Semantically segmented image of the person to be authenticated is used as the cover image and chaotic encrypted fingerprint image is used as secret image here. Chaotic encrypted fingerprint image is embedded into the cover image using Integer Wavelet Transform (IWT). Extracted fingerprint image is then compared with the fingerprints in database to authenticate the person. Qualified Significant Wavelet Trees (QSWT`s) of the cover image act as the target coefficients to insert the secret image. IWT provide both invisibility and resistance against the lossy transmissions. Experimental result shows that the semantic segmentation reduces the bandwidth efficiently. In addition, chaotic encryption and IWT based data hiding increases the security of the transmitted biometric data.