Steganography Algorithm Based on the Nonlocal Maximum Likelihood Noise Estimation for Mobile Applications

In recent years, thanks to the use of Internet services, daily activities used to imply movement became more accessible to any user. As a result of such interconnection, now millions of people from different countries are able to communicate among themselves through the Internet, generating a great flow of data and classified information. The information on the Internet can be stolen, intercepted, anonymized, or even destroyed, resulting in cases of infringement of intellectual property rights, and the loss or damage of data. In such a globalized and interconnected world, solid security measures have become increasingly important to ensure data privacy protection and its confidentiality during transit. Nowadays, there is a variety of security mechanisms such as the steganography, an information hiding technique, which protects intellectual property by allowing the transmission of hidden data without drawing any suspicion. In order to achieve these criteria, an adaptation of the nonlocal maximum likelihood filter is proposed; in this class of filters, in general, they are used in images that require a high level of irregular pattern detection, based on the statistical dependence of the underlying pixels of the image analysis area, when using it in the wavelet domain as edge detector and/or discontinuities in images in order to have a greater selectivity when inserting information in the image. It strengthens the detection of the areas with the highest probability of having noise presenting results which are suitable areas to insert the information and that it is imperceptible in a quantitative and qualitative manner as presented in the Results and Discussion.