The last few decades have seen a tremendous growth in computing machines as well as the digital information with internet expansion. The transmission and storage of this huge volume of information is a high priority issue and has lead to the evolvement of information hiding and cryptographic techniques. Cryptography scrambles the message to be transmitted safely and different key sizes implement different security levels. Steganography is an information hiding technique and embeds the information in undetectable files like images or texts such that their very presence is not detected with the naked eyes. Cryptography and steganography have their own advantages and disadvantages and though each is resistant to attacks in their own ways, a combination of both results in a better cryptosystem and is a chief domain of research these days. Completely different from other methods, this paper makes use of the basic traits of statistical distribution given by mean and standard deviation; the basic building block for this paper. Embedding is done by adopting LSB substitution and PI. Bits to be infixed are decided by some prerequisites for increasing ramification. Justification for this algorithm is given by rudimentary of images along with bits per pixel and capacity of embedding. This paper promises high security and enhanced robustness as well.
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Science redeems itself with inventions, redefining its dimensions with time. These new technologies and new applications not only help us but also bring with it many new threats. Thus, it is the need of the hour for the protection mechanisms to keep re-inventing itself along with their respective technologies. When businesses started to build networked computer systems, Cryptography became important (Salem et al., 2011; Schneier, 2007). Increased usage of PCS for communication led to virus outbreak and thanks to Internet, Firewall diligence got profited. Information Security, right now (Amirtharajan et al., 2012; Janakiraman et al., 2012a, b; Rajagopalan et al., 2012; Thenmozhi et al., 2012) has become a buzzword, with government drawing up laws to intensify surveillance and copyright infringements, making life difficult for media houses (Stefan and Fabin, 2000).
With the growing popularity of MP3 encoded music and the perfection with which copies of digital music and video are made, the entertainment industry has become nervous that their content might be pirated much more than what currently happens with analogue home taping (Stefan and Fabin, 2000). In the course of recurrent acclivity, networking protocols, online check, trial of buccaneers, software commerce has dumped copy control. But as for music and video, technical protection mechanisms plays a vital role, of these mechanisms is copyright marking-hiding copyright notices and serial numbers in the audio or video so that pirates find it difficult to remove (Abdulfetah et al., 2010; Stefan and Fabin, 2000; Zeki et al., 2011).
One can think of encryption methodologies making wiretapping thorny for government bureaus; their common reaction is to try to restrict the strength of encryption algorithms or require that spare copies of the keys are available somewhere for them to seize (Salem et al., 2011; Schneier, 2007). On the other hand, the advocates of Civil liberties are outraged at this and declared it as an intolerable assault on privacy. But most police communication intelligence is not about wiretapping, so much as tracing networks of contacts. The prepaid mobile phone is the typical criminal communications tool. Criminals also hide their communication using the kind of techniques developed for copyright marking but the issue is not the secrecy of communications but their trace-ability.
Information hiding and security is very crucial for exclusive rights (Stefan and Fabin, 2000) and discretion. At times, researchers de-identify the personal information of people for processing while other times it is possible to re-identify the data subjects without too much effort. Because of so many forces driving it, research in information hiding has seen an exponential growth (Zaidan et al., 2010). What has been achieved in the field of cryptology from 1945-1990 (45 years) has been achieved by information hiding in the last 13 years (Stefan and Fabin, 2000).
A lot of experiments have been done (Amirtharajan et al., 2011, 2012; Cheddad et al., 2010; Gutub, 2010; Hmood et al., 2010a, b; Luo et al., 2011; Mohammad et al., 2011; Padmaa et al., 2011; Thanikaiselvan et al., 2011a, b; Zanganeh and Ibrahim, 2011; Zhao and Luo, 2012, EI-Safy et al., 2009); a large number of systems have been proposed; many of them have been broken. And as a result we now have a fair idea of what works, what doesn't and where the interesting and successful research directions are. And we can now be sure Information Hiding is the key to avoid many of the new threats.
Water marking and Steganography are two major division of Information Hiding. Classification of Steganography is as shown in the Fig. 1. Further classification can be (Stefan and Fabin, 2000), as per key, pure, secret and public key steganography. Linguistic and Technical steganography can also be stated as steganographys division. Based on the medium used for hiding (Bender et al., 1996), steganography can be segmented into Text (Al-Azawi and Fadhil, 2010; Xiang et al., 2011), Video (Al-Frajat et al., 2010), Audio (Zhu et al., 2011) and Image steganography (Amirtharajan and Rayappan, 2012a-d; Amirtharajan et al., 2012; Chan and Cheng, 2004; Zhao and Luo, 2012). This paper proposes a novel method for variable bit embedding through statistics of the cover pixel blend with pixel indicator to offer high payload and imperceptibility.
This is a plan to incorporate variable bit embedding through the cover statistics. First calculate the Mean and Standard deviation of 4 MSBs of every pixel of the entire image.
|Fig. 1:||Flow chart for classification of steganography|
|Fig. 2:||Block diagram for proposed system|
If the pixel intensity value is less than (mean-SD/2), then 2 bits are embedded, otherwise if value is less than (mean+SD/2) 3 bits are embedded, else 4 bits are embedded. Random traversing path is used for embedding to increase disorderliness. The schematic for this study is given in Fig. 2 and flowcharts for embedding and extraction of secret information is shown in Fig. 3 and 4.
|Fig. 3:||Flow chart for embedding|
|Fig. 4:||Flow chart for extraction|
RESULTS AND DISCUSSION
For experimental analysis, Lena, baboon, temple and Mahatma Gandhi of 256 x256 x3 are taken as cover as in Fig. 5a,b,c and d, respectively. As per the algorithm, the bits for embedding vary from 2 to 4.
|Fig. 5(a-d):||Cover images, (a) Lena, (b)Baboon, (c) Mahatma Gandhi and (d) Temple|
|Fig. 6(a-d):||Stego images, (a) Lena (b), Baboon, (c) Mahatma Gandhi and (d) Temple|
Before embedding, each cover image submits itself to manipulation by means of conversion of matrix and modulo. The traversing path is decided by the pseudo random generator. Hence the cover image undergoes subsequent alterations even before embedding. The idea of computing mean and standard deviation also increases the complexity. The stego images of Lena, baboon, temple and Mahatma Gandhi are shown in Fig. 6a, b, c and d respectively. The histograms for both cover and stego images of Lena, baboon, temple and Mahatma Gandhi are publicized in Fig. 7a-d, respectively.
Higher PSNR indicates that the stego images are of high quality and does not seek the interest of the invader because of nil visual artifacts. MSE and PSNR are given by:
|M,N||=||Dimensions of the image|
|Ci, j||=||The pixels in the original image|
|Si, j||=||The pixels of the stego-image|
where, for color image Imax = 255.
|Fig. 7(a-d):||Histogram of cover and stego images before and after embeding, (a) Lena, (b) Baboon, (c) Mahatma Gandhi and (d) Temple|
From the Table 1, we can infer the fact that more bits are embedded in each cover image. Since, RED is the default indicator here in this algorithm, the bits per pixel value is calculated is computed for each data channel is depicted. Apart from the table and output images, the histograms of the covers and their respective stego outputs confirm the efficiency and competence level.
|Table 1:||MSE, PSNR, BPP values for proposed method|
In this study a new way of image steganography is done with creative thinking. Using pixel indicator method, modulus function and pseudorandom generator resulting in a distinct embedding process, traversing path is calculated with the support of pseudorandom generator. The parameters such as mean square error, peak signal to noise ratio, bits per pixel and embedding capacity are measured for a stego-image, found to be marvelous. Since tracing the pseudorandom alignment is hectic, attacks posed on this algorithm is awful. Hence one cannot modify the content and attempts for doing so go vain. This new steganography forms a high quality stego-image as compared with the existing ones, it boasts that it can repel over any type of attacks and provides privacy as well as secure communication.
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