Design of Steganographic Applications in A Processed Image using Algorithm Dynamic Markov Compression

−Confidential text data is an important matter that needs to be protected and kept confidential. Secret text data is a treasure where many people who want to try to find out first find out its contents. Therefore it is not uncommon for crimes to appear intentionally committed by irresponsible people. With the increasing number of people who commit crimes who deliberately steal confidential data and damage confidential text data so that it can harm certain parties. There have been several attempts to deal with the issue of security of confidential data sent over the internet, including using cryptographic and steganographic techniques.


INTRODUCTION
Confidential text data is an important matter that needs to be protected and kept confidential. Secret text data is a treasure where many people who want to try to find out first find out its contents. Therefore it is not uncommon for crimes to appear intentionally committed by irresponsible people. With the increasing number of people who commit crimes who deliberately steal confidential data and damage confidential text data so that it can harm certain parties. There have been several attempts to deal with the issue of security of confidential data sent over the internet, including using cryptographic and steganographic techniques. Cryptography is the study of how to maintain the confidentiality of data, keeping data or messages safe when sent, from sender to recipient without experiencing interference from third parties. (Ahmad Ramadoni Sitorus, Volume: iv, Number: 3, October 2014). While steganography (steganography) is the science and art of hiding secret messages in messages so that the existence of the secret message cannot be known [1].
Steganography is one of the techniques used in securing information, namely by hiding information into digital media with certain methods. So that no visual difference between the original file and the file that has been inserted information (stegoimage). So it is not known by people who can solve stegoimage without knowing the existing key. Digital data that can be a place or media data that will be hidden in steganography are images / images, audio and video [2].

Steganography
Steganography (Steganography) is the science and art of hiding secret messages in other messages so that the existence of the secret message cannot be known. Steganography comes from the Greek language that is steganos which means hidden writing. Steganography is very contrast with cryptography. If cryptography conceals the meaning of the message while the existence of the message persists, then steganography covers the existence of the message. Steganography can be seen as a continuation of cryptography in practice secret messages are first encrypted, then ciphertext is hidden in other media so that third parties are not aware of its existence. The hidden message can be extracted back exactly the same as the original.

Compression
The compression process is the process of reducing the size of a data to produce a digital representation that is dense or incompressible but still can be represented by the quantity of information contained in the data. In imagery, video and audio, compression leads to minimization of the number of bit rates for digital representation. In some literature, the term compression is often also called source coding, data compression, bandwidth compression and signal compression.

Huffman Algorithm
Huffman algorithm is an image compression algorithm that uses a statistical approach. The sequence of steps to encode this algorithm is as follows. 1. Sort garyscale values based on frequency of occurrence.

RESULT AND DISCUSSION
The system analysis phase is the decomposition of a whole information system into its component parts with the aim of identifying and evaluating problems, opportunities, constraints and expected needs so that improvements can be proposed.

Embedded Process / Message Insertion
The workings of the Last Sihgnificant Bit (LSB) method in steganography are as follows: 1. Convert the image to be inserted into binary form 2. Convert the value of the degree of gray image level into binary numbers in the form of a matrix. 3. Take the bits of each byte of the image to be inserted into the binary blocks of the image as the container. 4. The inserted image bits will be placed at the end of the binary image by replacing the binary of the image in accordance with the bits of the inserted image 5. The image that has been inserted is called a stego image The embedded message stage is the stage of inserting a message into a media container with the aim of hiding the message so that it is not seen or known by others who are not entitled to know it.

Message Extraction / Disclosure Process
Then, after inserting with the Last Sihgnificant Bit (LSB) method, the extraction / disclosure of the stego image will be performed to retrieve the image / message that has been inserted. The workings of the Last Sihgnificant Bit method in the process of disclosing the message are as follows. 1. Convert the stego image value to binary numbers in the form of a matrix. 2. Then match each stego image block with the inserted binary image 3. If appropriate, the image that has been inserted will be retrieved and can be proven.

Application of Dynamic Markov
Here's how the encoding and decoding of the Dynamic Markov compression algorithm works with the characters from the existing image matrix as follows:   1111111 1010011 111011 1010101 11 0001001 1 110101 1011111 1100011 0111. Because the numbers 0 and 1 represent 1 bits, so the data bits above consist of 30 bits in other words the image size after compression using Dynamic Markov is 89 bits.

Application of the Least Significant Bit (LSB) Method
Suppose the message you want to insert is a 2 x 2 image = 4 pixels. The binary value above will be inserted into the image which will later be converted into a binary value. For example. Taken color images as the insertion media secret message, as follows.

Embedded / Message Insertion
For the first steganographic process is the first pixel value of "193" whose binary value is "11000001". The last digit of the image bit will be replaced by the first bit value of the secret message bit.  28  00011100 inserted 0  00011100 Unchanged  27  00011011 inserted 0  00011010 26  26  00011010 inserted 1  00011011 27 Furthermore, the steganography process of the second pixel value is "194" whose binary value is "11000010" The last digit of the image bit will be replaced by the first bit value of the secret message bit. 00011010 inserted 0 00011010 Unchanged Furthermore, the steganography process of the third pixel value is "195" whose binary value is "11000011" The last digit of the image bit will be replaced by the first bit value of the secret message bit. 00010110 inserted 1 00010111 23 Furthermore, the steganography process of the fourth pixel value is "195" whose binary value is "11000011". The last digit of the image bit will be replaced by the first bit value of the secret message bit.  27  27  24  24  24  28  26  27  25  25  26  24  26  24  25  26  25  29  24  24  24  24  23  23  23  22  23  22  21  22  23 23 21 20 20

Stego Image Extraction / Disclosure
After doing the embedded process, it is necessary to disclose the secret message so that it can be read by the recipient or user of the message, as follows: This display will display the process of inserting messages into a grayscale image. b. Insert and save button to save the ordered grayscale image. c. Exit button to exit the display. In this view the process of decompressing the image will be displayed. As shown in the following image.