An LSB Data Hiding Technique Using Natural Numbers

In this paper, a novel data hiding technique is proposed, as an improvement over the Fibonacci LSB data-hiding technique proposed by Battisti et al,based on decomposition of a number (pixel-value) in sum of natural numbers. This particular representation again generates a different set of (virtual) bit-planes altogether, suitable for embedding purposes. We get more bit-planes than that we get using Prime technique.These bit-planes not only allow one to embed secret message in higher bit-planes but also do it without much distortion, with a much better stego-image quality, and in a reliable and secured manner, guaranteeing efficient retrieval of secret message. A comparative performance study between the classical Least Significant Bit(LSB) method, the Fibonacci LSB data-hiding technique and the proposed schemes indicate that image quality of the stego-image hidden by the technique using the natural decomposition method improves drastically against that using Prime and Fibonacci decomposition technique. Experimental results also illustrate that, the stego-image is visually indistinguishable from the original cover-image. Also we show the optimality of our technique.Comment: 6 Pages, 5 Figures, IEEE Third International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIHMSP 2007, Nov 26-28, 2007, Kaohsiung City, Taiwan, IEEE Computer Society press, USA, ISBN 0-7695-2994-1, pp. 473-476, 2007

Coverless image steganography using morphed face recognition based on convolutional neural network

In recent years, information security has become a prime issue of worldwide concern. To improve the validity and proficiency of the image data hiding approach, a piece of state-of-the-art secret information hiding transmission scheme based on morphed face recognition is proposed. In our proposed data hiding approach, a group of morphed face images is produced from an arranged small-scale face image dataset. Then, a morphed face image which is encoded with a secret message is sent to the receiver. The receiver uses powerful and robust deep learning models to recover the secret message by recognizing the parents of the morphed face images. Furthermore, we design two novel Convolutional Neural Network (CNN) architectures (e.g. MFR-Net V1 and MFR-Net V2) to perform morphed face recognition and achieved the highest accuracy compared with existing networks. Additionally, the experimental results show that the proposed schema has higher retrieval capacity and accuracy and it provides better robustness

A Taxonomy of Hyperlink Hiding Techniques

Hidden links are designed solely for search engines rather than visitors. To get high search engine rankings, link hiding techniques are usually used for the profitability of black industries, such as illicit game servers, false medical services, illegal gambling, and less attractive high-profit industry, etc. This paper investigates hyperlink hiding techniques on the Web, and gives a detailed taxonomy. We believe the taxonomy can help develop appropriate countermeasures. Study on 5,583,451 Chinese sites' home pages indicate that link hidden techniques are very prevalent on the Web. We also tried to explore the attitude of Google towards link hiding spam by analyzing the PageRank values of relative links. The results show that more should be done to punish the hidden link spam.Comment: 12 pages, 2 figure

A review on medicinal properties of saffron toward major diseases

The stigma of Crocus sativus, known as saffron, is one of the most expensive spices in the world. The bioactive components in saffron, picrocrocin, crocin, and safranal, have demonstrated a wide range of uses and capabilities in the medical field. This review is focused on the potential therapeutic applications of saffron on diabetes mellitus (DM), antitumor, anticancer, anti-depressant, Alzheimer’s disease (AD), cardiovascular disease (CVD), erectile dysfunction and antibacterial effects

Multilayer Reversible Data Hiding Via Histogram Shifting

Concealing messages from unauthorised people has been desired since written communication first began. With advancements in digital communication technology and the growth of computer power and storage, the difficulty of ensuring the privacy of individuals and the protection of copyright has become increasingly challenging. Steganography finds a role in attempting to address these growing concerns. Problems arise in the steganography method because of the trade-off between capacity and imperceptibility whereby increasing the embedding capacity increases the distortion in the stego object and it thus becomes suspect. Another problem is concerned with non-retrieval of the original cover object whereby misplacing data could be crucial for example in the case of medical images. Reversible data hiding technique based on histogram shifting addresses the problem of retrieving the original cover. Embedding the secret message by shifting the histogram between the pair of the peak and minimum points wastes the embedding capacity and does not control the distortion in the stego image for various secret messages sizes. In this research, a technique for reversible data hiding is proposed which enables the retrieval of both the hidden secret message and the original image at the receiver’s side. The proposed technique considers the size of the secret message and the distribution of the colour values within the cover image to determine the value of the optimal pair or set of container and carried colours within the best sub image instead of the pair of peak and minimum points. The experimental results show that the proposed technique increases the embedding capacity within the cover image and produces a stego image with a high peak signal-to-noise ratio value. In addition, the experimental results show that by using the proposed re-shifting and extraction formulas, the technique has the ability to extract the hidden data and retrieve the original images from the stego images. In comparison to the traditional histogram-shifting techniques, the proposed technique significantly improves the stego image quality and the embedding capacity. Thus, this research has contributed to two principles, namely improvements in capacity and quality