Abstract: In the ubiquitous computing world, data are accessed by everyone at any time anywhere. People want to perform their business and personal tasks on-line. A person always wants to be on communication for banking, shopping and learning. The attractive and faster access on line facilities have to concern the secrecy of the messages exchanged over the communication media. Besides the communicating parties, there is a chance for the intruder to access the secret data. Data should be secured such that no malicious user knows the presence of the secret data. Everybody in this universe needs a secret communication world. To satisfy the need of all the Internet users, information hiding technology has developed. The most powerful weapon to hide a secret message is steganography, which is older than cryptography. This study presents one more algorithm involving three easily implementable but complex procedures to increase the security during transmission of secret data. The routines are key value based k-bit embedding, embedding in line with Fibonacci series and by Shannon-Fano encoding, respectively. Each method follows an ideal procedure to encapsulate more secret information at the same time meeting other requirements for an idyllic transmission. The performance of this study is evaluated by means of MSE and PSNR and the results are tabled.
INTRODUCTION
Steganography appeared before cryptography. In the 5th century BC, King Darius used steganography for his communication. He used their political prisoners as cover medium and tattooed the secret message onto the shaven scalp of the prisoner. It becomes stego after hair grows. Wax tablets, invisible inks and microdots were also used for Steganography (Kahn, 1983). While Cryptography protects the contents of a message (Schneier, 2007), Steganography holds responsibility for defending information and communicating bodies (Stefan and Fabin, 2000; Bender et al., 1996, 2000). Traits of Steganography and that of Watermarking are almost alike. One of the main differences between these two techniques needs to be highlighted (Hmood et al., 2010a, b; Cheddad et al., 2010; Zaidan et al., 2010).
Digital watermarking ascertains no exclusion of or unchangeable watermark despite the fact of being bluntly evident (Stefan and Fabin, 2000). But Steganography, conversely, zooms in on masquerading secret information (Amirtharajan and Rayappan, 2012a-d).
| Fig. 1: | Embedding process |
But it falls short if the secret content is exposed by the interloper (Padmaa et al., 2011; Qin et al., 2010). The advancements in computer technology today have improved the electronic media such as text (Shirali-Shahreza and Shirali-Shahreza, 2008; Al-Azawi and Fadhil, 2010), image (Chan and Cheng, 2004; Thanikaiselvan et al., 2011; Rajagopalan et al., 2012; Janakiraman et al., 2012a, b), audio (Zhu et al., 2011) and video (Al-Frajat et al., 2010) used for the steganographic communication (Zanganeh and Ibrahim, 2011; Luo et al., 2008; Thenmozhi et al., 2012).
Image Steganography uses image as cover object by hiding the relevant information in the cover image so that avoiding the information to be exposed to an intruder (Stefan and Fabin, 2000; Amirtharajan and Rayappan, 2012a-d). Digital images are used as cover-images in steganography because of their higher propagation and higher degree of redundancy in steganography because of their higher propagation and higher degree of redundancy. Steganography possesses two vital imputes, namely, payload and sensitivity. Steganography utilizes human insight as human wits are not taught to search for records having veiled information. Therefore, steganography conceals data from hackers. Payload is the amount of the secret information a cover image has (Amirtharajan and Rayappan, 2012a-d).
At the transmitter end, the secret message is embedded into the cover image as shown in Fig. 1. At the receiver end, the stego image is extracted to get the original secret message. Fundamental principle of Steganography is to maneuver the cover file’s pixels and their corresponding values in succession, thus turning it to a code which is helpful in rebuilding the message while retrieving. This study tries to study the performances of 3 such suggested methods from Amirtharajan et al. (2012).
PROPOSED METHODOLOGY
In this study, three different embedding techniques such as k-bit embedding with a key, embedding based on Fibonacci series, embedding secret text encoded by Shannon-Fano encoding technique are implemented for information hiding. The MSE and PSNR for the above three methods have been calculated and tabulated. The pros and cons of the methods are also discussed in this study. Block diagram of this proposed technique is shown in Fig. 2.
Algorithm for k bit embedding with a key| Fig. 2: | Block diagram of proposed technique |
Figure 3 represents the flow chart for k-bit embedding with a key.
Algorithm for embedding based on Fibonacci seriesFigure 4 gives the flow chart for embedding based on Fibonacci series.
Algorithm for embedding secret text encoded by Shannon fano encoding techniqueFigure 5 represents the Flow chart for embedding secret text encoded by Shannon-Fano encoding technique.
| Fig. 3: | Flow chart for k-bit embedding with a key |
RESULTS AND DISCUSSION
To evaluate the performance of the implemented methods several experiments have been conducted, two image quality metrics are analysed are as follows. The MSE and PSNR values calculated for the proposed techniques are shown in the Table 1.
MSE: Mean square error this measures the signal to noise ratio. It is calculated from finding difference of intensities between cover image and stego image:
Where:
| M | = | No. of rows in the image |
| N | = | No. of columns in the image |
| Xi,j, Yi,j | = | Pixel intensity of the stego imagecover image. |
PSNR: Peak signal to noise ratio is calculated by finding the ratio between the maximum intensity and the distortion in the image after embedding:
where, Imax is maximum intensity of the image.
| Fig. 4: | Flow chart for embedding based on Fibonacci series |
| Fig. 5: | Flow chart for embedding secret text encoded by Shannon-Fano encoding technique |
As given in the table, rose image (cover image) of dimension 250x250 having the size of about 1.09 KB is taken for the execution of all the three methods. The MSE and PSNR values for individual plane for all the three methods are charted. For Fibonacci and Shanon Fano methods, the red plane has higher PSNR than blue and green. If judged against these two, the latter bids added imperceptibility than the former. It escapes human suspicion. Needless to mention here is the fact that in the first method entrenching takes place for chosen pixels only whereas in the second one, it is done for the entire pixels. In the K-bit embedding proposal, embedding is done by shifting the key values ranging from 2 to 14, whose MSE values face ups and downs in all the planes. As it is vivid, key value 2 tenders high imperceptibility of 58 dB than the rest which designates that it is fairly a high quality image.
The original covers and their resultant stego are given in Fig. 6a, b, 7a, b and 8a, b, respectively for three methods.
| Table 1: | Comparison table of three methods |
| Fig. 6(a-b): | Results for k-bit embedding for key value = 14 (a) Cover image and (b) Stego image |
| Fig. 7(a-b): | Results for embedding based on Fibonacci series, (a) Cover image and (b) Stego image |
| Fig. 8(a-b): | Results for embedding secret text encoded by Shannon-Fano encoding technique, (a) Cover image and (b) Stego image |
They have high degree of similarity which makes their characterization pretty hard. The fact of identification of secret data remains quite difficult. As a final point, this construct is capable of accomplishing soaring rate of capability, refuge and stoutness.
CONCLUSION
This study, rooted in K-bit embedding, Fibonacci series and Shannon-Fano encoding method projects a data masking algorithm apt for elevated privacy, capacity. By defining the strictures of selection or amount of pixels and key values, data is implanted adaptively as said by the algorithm. In this fashion, it circumvents huge deformation and can push in extra surreptitious data. This upshot offers the leeway of safe and sound conduction of desired information through computer. Tentative results prove that this anticipated scheme validates the conclusion and without doubt surpasses the former plots. Hence, this method is a viable means for covert communication.