An Innovative Method of Text Steganograph

An Innovative Method of Text Steganograph

AbstractSteganography is a technique where data is hidden within data .There are various kinds of steganography depending on what type of covering media I used to hide a secret message. They are video steganography, image steganography, audio steganography and text steganography. In this paper various techniques proposed for text steganography is studied.

KeywordsDWT, IDWT ,Text steganography, PSNR, Stegoimage

1. INTRODUCTION

   In text steganography, there are two processes involved. They are embedding process and extraction process. In embedding process a secret message is hidden inside a cover message and in extraction process a secret message is recovered from the cover message.

   Various kinds of steganography are video steganography, image steganography, audio steganography and text steganography.

   Video Steganography is a technique to embed a secret message in a video by altering the BCH coding, quantization scale etc. For example to hide text in a video, a lot of space and processing time is required. The input video stream is changed as per the secret message and the altered bit stream is converted into final video for transmission.

   Image steganography is a technique to hide information inside an image. Most widely used application of image steganography is in copywriting an image i.e. to hide the owners information inside an image. The image resolution and color can change when image steganography is performed.

   Audio steganography is a technique to hide information inside an audio file. Most widely used application of audio steganography is in sound watermarking i.e. to hide owners information inside an audio file. The audio resolution can change when audio steganography is performed.

   Text steganography is a technique to hide a text message within a cover text message. This technique is mostly used to hide confidential messages confidential missions, bank credentials etc.

   on a hash function. The algorithm has two parts, one is embedding algorithm and another is extracting algorithm. The following section describes the embedding and extracting process.

   A.Embedding Process

   On the letters in the secret message (SM), an encoding technique called as Gödel function is applied. In Gödel function for each letter in SM, a pair of numbers is generated based on its ASCII code. These two numbers generated are termed as and and are unique to the letter in SM. In is the ASCII value of letter in SM, and satisfies the following equation, < , > = 2 (2 + 1) 1, where 2 (2 +

   1) 0. is the largest number such that ( + 1) / 2 must be odd and = [(( + 1) / 2) 1]/2. After producing and , both are converted into 6 bit binary strings and joined to produce 12 bit binary string. To generate a symmetric key, hash function is used. The Sending time (MS_SK) is obtained (for example 12:15) and 4th digit of the time is omitted a number is created (for example 121). This is converted into a 8 bit binary string and the Secret key (SK) is repeated while the length of the secret key binary string is greater than or equal to the length of the SM binary string.

   Later the embedding algorithm generates a hidden message by replacing each 2 bit by one zero width character (ZWC) as shown in below table.

   The following figure shows the pseudo code for the embedding algorithm.

2. EASE OF USE

I Text steganography Techniques

1. AITSteg

   AITSteg is a text steganography technique to transmit a hidden text by way of social media. AITSteg is a symmetric key based algorithm and the secret message is hidden based

   B.Embedding Process

   The extraction algorithm divides the secret message binary string into 12 bit groups and obtains and and then generates the ASCII character from and . The following figure shows the pseudo code of extraction algorithm.

2. AH4S

   AH4S is an algorithm for text steganography based on omega networks..

   1. Embedding process

      The structure of omega network is used to generate the cover message for a secret message. The following figure shows the structure of omega network.

      All the character in the secret message is read sequentially and is passed through the omega network to generate two cover characters. The omega network has two possibilities for the secret message so a random character is chosen amongst the two. The dictionary is searched to find a suitable word containing these two cover characters. A 12 digit key is generated for every word before transmitting by

      the embedding process. The structure of the generated key is as described below.

      The 1st digit in the key decides if first cover character is first one or the second character inside the input stage node in the omega network and similarly the 2nd digit if second cover letter is first one or second inside the output stage node of the omega network. The 3rd digit decides if the secret letter is a capital letter or not. The 4th to 7th digit is used to memorize the position of the first cover character. Similarly the 8th to 11th digits to memorize second cover characters position. The last position is used to determine if the secret character is at the end of the secret word or not.

      To hide the key string inside the cover message, white space steganography is used. An error control value is generated to add to the final cover word.

   2. Extraction process

   In extraction process the key error detection is done to make sure the correctness of the key. The cover characters are extracted from cover message and the secret character is found using the structure of the omega network. The following figure shows the flow in the omega network.

   .

3. Text Steganography based on Discrete wavelet transform

   This algorithm is based on DWT. The embedding and extraction process is described in the following section.

   1. Embedding process

      An input image and a secret text is input to the embedding algorithm. The text is converted to a binary string and DWT is applied on the image.

      The detailed coefficients of the DWT are selected and the data hiding process is applied on the detailed coefficients and on the secret message binary string. Now Inverse DWT is applied to get the stego-image.

   2. Extraction process

      The received stego-image is input to a decoder and DWT is applied on it. A message retrieval algorithm is applied on stego and cover image. On applying Inverse DWT the secret message is obtained.

4. Text Watermarking in Social media

   In this method, the original text is encoded using confusable symbols. These symbols are called Unicode homoglyphs. The following set of Unicode homoglyphs is used in this technique.

   When a confusable letter is found, the above table is used for encoding and the final string is shared on the social media.

5. Text Steganography using Daily Emotions Monitoring

   In this technique an emoticon is used to send a secret message.

   1. Embedding process

      A random key is selected and based on the key for each letter an emoticon is selected and final messageis prefixed with Today I Felt: string and a random timestamp is added after the emoticons. The following table shows the keys to convert a message into an emoticon.

   2. Extraction process

      The extraction process involves generation of the secret message in exactly opposite way of embedding process. Selection of wrong key results in generation of gibberish secret messages.

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