User data privacy in multimedia domain using 3–3 LSB-based color image steganography with RC4 and Bernoulli map protection

Abstract

Social media sites such as Facebook, Twitter, etc. have become commonplace in everyday life. With the emergence of the internet, the amount of data being created and communicated within social networks has increased exponentially. As much as we enjoy the exchange of information that occurs on social media, protecting and maintaining privacy demands a lot of effort. Users’ data that are to be kept private should be treated as confidential information. As a result, securing data exchange on the internet has become a critical and urgent issue. We have suggested a method for protecting user data which is encrypted by using the Rivest Cipher 4 (RC4) algorithm in multimedia images with the help of 3–3 least significant bits (LSB) techniques, with the added safety of Bernoulli map. We call this technique the “user data protection scheme.” 3–3 LSB is a message hiding process in which the first three stand for three LSB and the next three stand for all three channels (R, G, and B). In this method, we are using the Rivest Cipher 4 (RC4) encryption algorithm to encrypt the user’s data, which will then be embedded into the multimedia image in the next step. With the help of the Bernoulli map, we generate a random sequence of length similar to the size of the image. For every random number generated by the Bernoulli map, we determine the location in the plane and place three bits of secret message into the cover image using the LSB technique. Since we have used two different encryption techniques, i.e., RC4 for encryption of user data and Bernoulli map for embedding encrypted data at random locations over the cover image, our method is more secure than others. We performed this analysis to equate peak signal-to-noise ratio (PSNR) and mean square error. Our experimental result shows that 9 bpp can be embedded in color images with a PSNR higher than 42 dB, and for the gray scale image embedding capacity is 3 bpp with a PSNR higher than 42 dB, which provides better results. Apart from this, it produces less distorted stego-images than currently used methods (an average of 1.68 bpp).