MATLAB Projects of Digital Image processing, Audio Processing, Video Processing and Basics of MATLAB: MATLAB code of Analysis of LSB Based Steganography.

INTRODUCTION:

Information hiding in digital images has drawn much attention in recent years. Secret message encrypted and embedded in digital cover media. The redundancy of digital media, as well as characteristics of the human visual system, makes it possible to hide secret messages. Two competing aspects are considered while designing information hiding scheme

1) Hiding capacity and

2) Imperceptibility.

Hiding capacity means maximum payload. Imperceptibility means keeping undetectable. A least significant bits (LSB) substitution method is widely used for hiding data in digital images. This method widely used because of large capacity and easy implementation. Cryptography was created as a technique for securing the secrecy of communication and many different methods have been developed to encrypt and decrypt data in order to keep the message secret. Unfortunately it is sometimes not enough to keep the contents of a message secret, it may also be necessary to keep the existence of the message secret. The technique used to implement is called steganography. It is the art and science of invisible communication. The advantage of steganography over cryptography alone is that messages do not attract attention to themselves, to messengers, or to recipients. Steganographic messages are often first encrypted by some traditional means, and then a cover text is modified in some way to contain the encrypted message, resulting in stego text. This is a technique to embed additional message into some distortion-unacceptable cover media, such as military or medical images, with a reversible manner so that the original cover content can be perfectly restored after extraction of the hidden message.

IMAGE into IMAGE Steganography:

In this method we hide binary image into grayscale or color image. In this method our aim is to hide secrete binary image into grayscale or color image.

first step is to encrypt secrete image with secrete key. This can be achieved with the help of xor function. XORing of secret message and generated key stream will complete the encryption process.

LSB (Least significant bit) substitution:

Least significant bit (LSB) insertion is a common, simple approach to embedding information in a cover image. The least significant bit (in other words, the 8th bit) of some or all of the bytes inside an image is changed to a bit of the secret message. When using a 24-bit image, a bit of each of the red, green and blue color components can be used, since they are each represented by a byte. In other words, one can store 3 bits in each pixel. An 800 × 600 pixel image, can thus store a total amount of 1,440,000 bits or 180,000 bytes of embedded data. This Principle involved in this method is to replace all LSB bits of pixels of the cover image with secret bits. This method embeds the fixed length secret bits in the same fixed length LSBs of pixels. Although this technique is simple, it generally causes noticeable distortion when the number of embedded bits for each pixel exceeds three.

Image Transmitter Image Receiver

From extraction we will get only encrypted message but to identify secret message decryption process is used, for decryption of secret message we require same key stream that we have used at transmitter for encryption of message. After decryption process user will get information from secret message.

TEXT into IMAGE Steganography:

In text steganography we first convert text from text to binary then we encrypt that binary stream with secrete key and then we hide that encrypted binary stream to LSBs of the cover image with the help of LSB substitution method. At receiver side we do exactly opposite process for getting original text back.

Text Transmitter Text Receiver

Result Analysis and Discussion:

Following results are obtained for Lena Image with the devi image. The terms in table are EC = Embedding capacity, NBE = Number of bits embedded, PSNR = Peak signal to noise ratio.