Literature Review About Cryptography And Steganography Computer Science Essay Example

encrypted form, but draws much lesser interest being allocated in the images then it would otherwise.

This becomes mainly significant as the technological discrepancy between individuals and institutions grows. Governments and businesses usually have access to more powerful systems and better encryption algorithms then individuals. Hence, the possibility of individual’s messages being broken increases with each passing year. Decreasing the quantity of messages intercepted by the associations as suspect will definitely facilitate to progress privacy.

An additional benefit is that information hiding can basically alter the way that we consider about information security. Cryptographic schemes usually depend on the metaphor of a portion of information being placed in a protected “box” and locked with a “key”. Anyone can get access with the proper key as information itself is not disturbed. All of the information security is gone, once the box is open. Compare it with information hiding schemes in which the key is inserted into the information itself.

This contrast can be demonstrated in a better way by current DVD encryption methods. Digitally encoded videos are encapsulated into an encrypted container by CSS algorithm. The video is decrypted and played when the DVD player supplies the proper key. It is easy to trans-code the contents and distribute it without any mark of the author present, once the video has been decoded. On the other hand the approach of an ideal watermark is a totally different, where regardless of encryption the watermark remains with the video even if various alteration and trans-coding efforts are made. So it is clarifies the need for a combination of the two schemes.

Beginning with a swift tour on cryptography and

steganography, which structure the foundation for a large number of digital watermarking ideas then moving on to a description that what are the prerequisites a watermarking system must meet, as well as techniques for estimating the strengths of different algorithms. Last of all we will spotlight on various watermarking schemes and the pros and cons of each. Even though most of the focus is solely on the watermarking of digital images, still most of these same concepts can straightforwardly be applied to the watermarking of digital audio and video.

Background

First of all we begin with some definitions. Cryptography can be described as the processing of information into an unintelligible (encrypted) form for the purposes of secure transmission. Through the use of a “key” the receiver can decode the encrypted message (decrypting) to retrieve the original message.

Stenography gets better on this by concealing the reality that a communication even took place. Hidden Information message m is embedded into a harm less message c which is defined as the cover-obect. With the help of key k which is called as stego-key the hidden message m is embedded into c. The resulting message that is produced from hidden message m, the key k and the cover object c is defined as stego-object s. In an ideal world the stego-object is not distinguishable from the original message c, seems to be as if no additional data has been embedded. Figure 1 illustrates the same.

Figure 1- Illustration of a Stegographic System

We use cover object just to create the stego object and after that it is disposed. The concept of system is that stego-object will almost be same

in look and data to the original such that the existence of hidden message will be imperceptible. As stated earlier, we will suppose the stego object as a digital image, making it clear that ideas may be expanded to further cover objects as well.

In a number of aspects watermarking is matching to steganography. Each of them looks for embedding information into a cover object message with almost no effect to the quality of the cover-object. On the other hand watermarking includes the extra requirement of robustness. A perfect steganographic system would tend to embed a huge quantity of information, ideally securely with no perceptible degradation to cover image. A watermarking system is considered to be n ideal which would inject information that cannot be eliminated/modified except the cover object is made completely unusable. After these different requirements there is a reaction, a watermarking scheme will frequently deal capacity and perhaps even a little security for extra robustness.

Then a question arises that what prerequisites might a perfect watermarking system should have? The primary constraint would obviously be that of perceptibility. A watermarking system is useless if it degrades the cover object to the extent of being of no use, or even extremely disturbing. In an ideal scenario the water marked image should give the impression of being identical from the original even if it is viewed on the best class device.

A watermark, considered to be ideal, must be highly robust, exclusively resistant to distortion when introduced to unintended attack while normal usage, or a intentional efforts to immobilize or eliminate the embedded watermark ( planned or malicious attack ). Unpremeditated attacks include alterations

that are usually implemented to images while usual usage, such as scaling, contrast enhancement, resizing, cropping A?a‚¬A¦etc.

The most interesting form of unintended attack is image compression. Lossy compression and watermarking are naturally at contrasts, watermarking try to encode hidden data in spare bits that compression tends to eliminate. So perfect watermarking and compression schemes are likely naturally restricted.

In malicious attacks, an attacker intentionally attempts to remove the watermark, frequently via geometric alterations or by embedding of noise. A last thing to keep in mind is that robustness can consist of either flexibility to attack, or complete delicateness. It is the case in which various watermarking schemes may have need of the watermark to entirely demolish the cover object if any tampering is made.

One more characteristics of ideal watermarking scheme is that it apply the implementation of keys to guarantee that the technique is not rendered ineffective the instant that the algorithm turns out to be recognized. Also it should be an aim that the method makes use of an asymmetric key scheme such as in public / private key cryptographic systems. Even though private key techniques are quite simple to apply in watermarking not like asymmetric key pairs which are normally not quite simple. The possibility here is that inserted watermarking scheme might have their private key found out, tarnishing protection of the whole system. It was just the scenario when a particular DVD decoder application left it’s secret key unencrypted, violating the whole DVD copy security system.

A bit less essential necessities of a perfect watermarking scheme might be capacity, and speed. A watermarking scheme must permit for a helpful quantity

of information to be inserted into the image. It can vary from one single bit to several paragraphs of text. Additionally, in watermarking schemes destined for embedded implementations, the watermark embedding (or detection) shouldn’t be computationally severe as to prevent its use on low cost micro controllers.

The final probable constraint of a perfect watermarking scheme is that of statistical imperceptibility. Watermarking algo must adjust the bits of cover in an approach that information of the image are not altered in any telltale style that may deceive the existence of the watermark. So it is not relatively lesser essential constraint in watermarking as compared to steganography but few applications might need it.

Then how to provide metrics for the assessment of watermarking methods? Capacity and pace can be simply estimated using the # of bits / cover size, and calculational complications, respectively. Use of keys by systems is more or less by characterization, and the informational indistinguishable by association among original images and watermarked equivalent.

The other complicated assignment is making metrics for perceptibility and robustness available. Standards proposed for the estimation of perceptibility are shown as in Table.

Level of Assurance
Criteria

Low

– Peak Signal-to-Noise Ratio (PSNR)

– Slightly perceptible but not annoying

Moderate

– Metric Based on perceptual model

– Not perceptible using mass market equipment

Moderate High

– Not perceptible in comparison with original under studio conditions

High

– Survives evaluation by large panel of persons under the strictest of conditions.

Table – Possible assurance stages of Perceptibility

Watermark must meet exposed minimum requirements the Low level in order to be considered handy. Watermarks at this stage should be opposing to general alterations

that non-malicious clients with economical tools might do to images. As the robustness enhances more specific and expensive tools turn out to be needed, in addition to extra intimate information of the watermarking scheme being used. At the very top of the scale is verifiable dependability in which it is also computationally or mathematically unfeasible to eliminate or immobilize the mark.

In this chapter a brief introduction of the background information, prerequisites and assessment methods needed for the accomplishment and estimation of watermarking schemes. In the next chapter a variety of watermarking techniques will be narrated and will be considered in terms of their potential strengths and weaknesses.

Selection of Watermark-Object

The most basic query that is required to think about is that in any watermark and stenographic scheme what sort of form will the implanted message will have? The most simple and easy consideration would be to insert text string into the image, permitting the image to straightly hold information such as writer, subject, timeA?a‚¬A¦and so on. On the other hand the negative aspect of this technique is that Ascii wording in a way can be well thought-out to be a appearance of LZW compression technique in which every character being characterized with a definite model of bits. Robustness of the watermark object suffers if compression is done prior to insertion.

As the structure of Ascii systems if a single bit fault is occurred due to an attack can completely alter the semantics of a certain letter and thus the hidden message is also changed or damaged. It would be fairly trouble-free for even a simple assignment such as JPEG compressing technique to trim

down a copy right string to a random set of typescript. Instead of characters, why not embed the information in an already highly redundant form, such as a raster image?

Figure 2 – Ideal Watermark-Object vs. Object with Additive Gaussian Noise

Note that in spite of the huge quantity of faults made in watermark discovery, the extracted watermark is still extremely identifiable.

Least Significant Bit Modification

The most uncomplicated technique of watermark insertion, is considered to be to embed the watermark into the least-significant-bits (LSB) of the cover object .Provided the surprisingly elevated channel capacity of using the whole cover for communication in this process, a smaller object may be embedded several times. Even if many of them are vanished due to attacks, only a one existing watermark is considered to be a success.

LSB replacement though in spite of its straightforwardness brings a crowd of weaknesses. Even though it may continue to exist if alterations such as cropping, noise addition or compression is probable to overcome the watermark. And an enhanced tamper attack will be basically to replace the lsb of every pixel by 1, completely overcoming the watermark with minor effect on the original image. In addition, if the algorithm is found out, the inserted watermark could be simply altered by an intermediary party.

An enhancement on fundamental LSB substitution will be to apply a pseudo-random digit initiator to decide the pixels to be utilized for insertion supported on a provided seed . Protection of the watermark will be enhanced as the watermark could not be simply observed by middle parties. The scheme still would be defenseless to the replacement of the LSBs with

a constant. Also if those pixels are used that are not utilized for watermarking bits, the effect of the replacement on the image will be insignificant. LSB alteration seems to be an easy and reasonably potent instrument for stenography, but is deficient of the fundamental robustness that watermarking implementations require.

Correlation-Based Techniques

An additional procedure for watermark insertion is to make use of the correlation characteristics of additive pseudo random noise patterns as applied to an image. A pseudorandom noise (P) pattern is embedded to the image R(i, j), as mentioned in the formula shown below.

Rw (i, j) = P (i, j) + k * Q(i, j)

Insertion of Pseudorandom Noise

k represents a gain factor & Rw is the watermarked image.

Amplifying k amplifies the robustness of the watermark at the cost of the excellence of the watermarked image.

To retrieve the watermark, the same pseudo-random noise generator algorithm is seeded with the same key, and the correlation between the noise pattern and possibly watermarked image computed. If the correlation exceeds a certain threshold T, the watermark is detected, and a single bit is set. This method can easily be extended to a multiple-bit watermark by dividing the image up into blocks, and performing the above procedure independently on each block.

In different of ways this fundamental scheme can be enhanced. 1st, the concept of a threshold being utilized for defining a binary ‘1’ or ‘0’ can be removed with the utilization of two different pseudorandom noise sequences. One sequence is allocated a binary ‘1’ and the second a ‘0’. The scheme which is mentioned previously is then carried out one time for every

sequence, and the sequence with the superior resulting correlation is exercised. It amplifies the possibility of a accurate discovery, still after the image has been considered to attack .

We can additionally enhance the technique by prefiltering image previous to implementing the watermark. If we can decrease the correlation among the cover image and the PN pattern, we can amplify the resistance of the watermark to extra noise. By implementing the edge improvement filter as given below, the robustness of the watermark can be enhanced with no loss of capability and with a very less lessening of image features.

Edge Enhancement Pre-Filter

Instead of defining the watermark values from ‘blocks’ in the spatial domain, we can make use of CDMA spread spectrum Schemes to spread every of the bits arbitrarily all over the original image, amplifying capability and enhancing immunity to cropping. The watermark is initially converted into a string instead of a 2 dimensional image. For every single pixel value of the watermark, a PN pattern is produced by making use of an self-sufficient key or seed. These keys or seeds could be stocked or created by itself via PN techniques. The addition of every one of the PN sequences stands for the watermark, which is then up sized and embedded to the original image .

To discover/extract the watermark, every seed/key is utilized to produce its PN pattern, which is after that correlated with the whole image. If it results with high correlation, then a bit of a watermark is assigned as ‘1’, else ‘0’. The same procedure is done again and again for each and every value of the watermark. CDMA enhances

on the robustness of the watermark considerably, but needs quite a few sequences further of calculation.

Frequency Domain Techniques

A benefit of the spatial domain methods has been talked about previously is that it can be simply implemented to any image, in spite of several type of intentional or unintentional attacks (though continuation to exist this alterations is totally a diverse issue). A probable drawback of spatial methods is that utilization of these subsequent alterations with the aim of amplifying the watermark robustness is not permitted by them.

Besides to this, adaptive watermarking schemes are a little extra tricky in the spatial domain. If the characteristics of the original image could correspondingly be utilized both the robustness and quality of the watermark could be enhanced. For the moment, instead of detail areas it is usually favorable to conceal watermarking data in noisy areas and edges of images. The advantage is 2 fold; it is extra perceivable to the HVS if degradation is done in detail areas of an image, and turns out to be a primary objective for lossy compression rechniques.

In view of these features, making use of a frequency domain turns out to be a bit more attractive. The traditional and yet well accepted domain for image processing is the Discrete-Cosine-Transform (DCT).

The Discrete-Cosine-Transform permits an image to be divided into different frequency bands, which makes it simple and easy to embed watermarking message into the mid frequency bands of an image. The reason behind selecting the middle frequency bands is that they have reduced even they evade low frequencies (visual areas of the image) exclusive of over-rendering themselves to elimination via compression and

noise attacks (high frequencies).

One of the methodologies makes use of the relationship of middle frequency band of DCT variables to encrypt a bit into a DCT block. Following 8?8 block shows the division of frequencies in terms of low, middle and high bands.

DCT Regions of Frequencies

FL represents the low frequency section of the block, whereas FH represents the higher frequency section.

FM is selected as the region where watermark is embedded so as to give extra immunity to lossy compression schemes, at the same time evading noteworthy amendment of the original image .

Then two positions Ai(x1, y1) and Ai(x2, y2) are selected from the middle frequency band area FM for evaluation. Instead of selecting random positions, if our selection of coefficients is according to the suggestion of JPEG quantization we can attain additional toughness to compression as given in the chart below. We can think positive that some sort of scaling of a coefficient will increase the other by the equal aspect if two positions are selected such that they have similar quantization values, which helps in maintaining their comparative ratio of size.

16

11

10

16

24

40

51

61

12

12

14

19

26

58

60

55

14

13

16

24

40

57

69

56

14

17

22

29

51

87

80

62

18

22

37

56

68

109

103

77

24

35

55

64

81

104

113

92

49

64

78

87

103

121

120

101

72

92

95

98

112

100

103

99

JPEG compression scheme quantization values

By observing the above chart we can see that coefficients (4,1) and (3,2) or (1,2) and (3,0) would formulate

appropriate contenders for contrast as we can see that there quantization values are similar. The DCT block will set a ‘1’ if Ai(x1, y1) > Ai(x2, y2), else it will set a ‘0’. The coefficients are then exchanged if the associative size of every coefficient does not agree with the bit that is to be encoded .

Because it is usually considered that DCT coefficients of middle frequencies contain analogous values so the exchange of such coefficients should not change the watermarked image considerably. If we set up a watermark “strength” constant k, in a way that Ai(x1, y1) – Ai(x2, y2) > k then it can result in the enhancement of the robustness of the watermark. Coefficients that do not meet these criteria are altered even if the utilization of arbitrary noise then convinces the relation. Mounting k thus decreases the possibility of finding of errors at the cost of extra image degradation.

An additional probable method is to insert a PN string Z into the middle frequencies of the DCT block. We can alter a provided DCT block p, q by making use of equation below.

Embedding of Code Division multiple access watermark into DCT middle frequencies

For every 8?8 block p,q of the image, the DCT for the block is initially computed. In that block, the middle frequency elements FM are incorporated to the PN string Z, multiply it by k the gain factor. Coefficients in the low and middle frequencies are copied over to the converted image without having any effect on. Every block is then contrary converted to provide us our concluding watermarked image OZ .