Local Features-Based Watermarking for Image Security in Social Media

The last decade shows an explosion of using social media, which raises several challenges related to the security of personal files including images. These challenges include modifying, illegal copying, identity fraud, copyright protection and ownership of images. Traditional digital watermarking techniques embed digital information inside another digital information without affecting the visual quality for security purposes. In this paper, we propose a hybrid digital watermarking and image processing approach to improve the image security level. Specifically, variants of the widely used Least-Significant Bit (LSB) watermarking technique are merged with a blob detection algorithm to embed information into the boundary pixels of the largest blob of a digital image. The proposed algorithms are tested using several experiments and techniques, which are followed by uploading the watermarked images into a social media site to evaluate the probability of extracting the embedding watermarks. The results show that the proposed approaches outperform the traditional LSB algorithm in terms of time, evaluation criteria and the percentage of pixels that have changed.