We are living in the era of information where billions of bits of data is created in every fraction

Data encryption and decryption have become increasingly important as more people are communicating over the internet. Although cryptology is not new, the demand for this technology has soared as its usefulness for security purposes has become more evident. Cryptology involves converting original messages into non-readable formats and plays an important role in keeping data safe while it is in transit (Agrawal & Mishra, 2012). Two popular forms of cryptology are symmetric and asymmetric.

In image steganography there are different kind of domains used for hiding information into a image and images are categorized in several types.

Steganography is art of hiding the secret message within an ordinary message and extraction of its destination. Steganography take cryptography a step farther by hiding an encrypted message so that no one finds the existence of the message. If anyone scans your data will fail to know that it contain encrypted data. Steganography maintain the secure communication between the communicating parties. There are different techniques that are used for hiding the secret data as Steganography, Cryptography and Watermarking. There are various drawbacks of the cryptography that are covered by the Steganography. This paper reviews the Steganography techniques and various matrices for performance analysis of Steganography techniques.

In the present world lot of multimedia data is exchanged on internet and the percent of image data in that is highest. So we need to securely transmit that and this can be achieved by Image encryption.

In this modern era, the computer and internet have becomes the most effective and fastest media for communication that connect different parts of the global world. As a result, people can easily exchange information and share information with the others via the internet. However, the information security requires the confidential data that needs to be protected from the unauthorized users. Steganography is one of the methods used for the secure transmission of confidential information. It can provide a high level of security to secure the important data during combined with encryption.

The core idea of this image encryption scheme (Tiegang Gao et al.,2007) is based on total shuffling matrix using the Logistic map, and the substitution of the shuffled image with a keystream

The process of Visual Cryptography, as developed through the original algorithm [12], was designed to be used with binary images. This is illustrated from the nature of the shares and the encryption process documented previously. If the secret messages being encoded contain text or binary images, the process shown in the original algorithm works well. However, the world is not composed of solely black and white pixels. With the increasing production of images in the digital age, gray and colour images have a pressing need for encryption and protection as much, or more, as binary images.

Abstract: Steganography is a kind of secret communication method used to hide secret data in some digital media such as images, audio etc. Cryptography and watermarking are other similar techniques. Data is secured using these methods, but the fact that data is present somewhere gives us a specific target, whereas sole purpose of steganography is that none must know there is some hidden data in the file. So, steganography easily has upper hand over cryptography and watermarking. Steganography can use almost all kinds of media present over internet to transmit secret data. In this paper, we review some audio steganography techniques, their algorithms and some challenges faced in their design and implementation. We will look in detail some modified techniques for audio steganography. Also, we look at the problems faced with using mp3 files as cover media.

Abstract – In this paper, we proposed an effective system for lossless image compression using different wavelet transform such as the stationary wavelet transform, the non decimated wavelet transform, and discrete wavelet transform with delta encoding and compare the results without delta encoding. With the development in the field of networking in the process of sending and receiving files needed to effective techniques for image compression as the raw images required large amounts of disk space to defect during transportation and storage operations. We used lossless compression to maintain the original features of the image in this process; there is a major problem which often is low compression ratios. We also use three types of wavelet transform which are discrete wavelet transform, non decimated wavelet transform, and stationary wavelet transform to demonstrate the effectiveness of the proposed system for comparison and to show the differences between each type to overcome previous challenges. This paper proposed a system for lossless image compression based on the use of the three types of wavelet transforms using Arithmetic coding and Huffman coding with delta coding, which helps in the high compression ratio to clarify the extent of the difference and distinction between each type. The results show that the stationary wavelet transform outperforms the non decimated wavelet transform and the discrete wavelet transform and with delta encoding outperforms without delta

Secret sharing is a scheme that permits a secret message to be shared among a set P of n participants. The secret is shared in such a way that only qualified subsets of P can recover the secret, any nonqualified subset has no information on the secret. We take into consideration, the problem of encrypting pictures and printed texts such that it is perfectly secure without the hassle of using cryptographic computations. In 1979, Shamir [7] and Blakley [8] introduced the concept of a threshold scheme. A (k, n) threshold scheme is a method whereby n pieces of information of a secret key k, called shares are distributed among n participants so that the k cannot be re constructed from the knowledge of fewer than k shares. In 1995 Naor and Shamir [1] proposed a new type of cryptographic scheme, which could encode and decode secret images without any cryptographic computations. The reason this scheme was considered remarkable was that the secret message

Two set of text images and one true sample image is taken for cryptography. In this proposed work these three images are encrypted into various shares through MATLAB, so that after compiling specific number of share the original image is visible. After encryption the performance analysis is done with the help of PSNR and MSE values.

The probabilistic model of the VC scheme was first introduced by Ito et al. [2], where the scheme is based on the basis matrices, but only one column of the matrices is chosen to encode a binary secret pixel, rather than the traditional VC scheme utilizing the whole basis matrices. The size of the generated transparencies is identical to the secret image. Yangs [31] also proposed a probabilistic model of VC scheme, and the two cases and are explicitly constructed to achieve the optimal contrast. Based on Yang [31], Cimato et al. [32] proposed a generalized VC scheme in which the pixel expansion is between the probabilistic model of VC scheme and the traditional VC scheme. Encrypting an image by random grids (RGs) was first introduced by Kafri and Keren [26] in 1987. A binary secret image is encoded into two noise-like transparencies with the same size of the original secret image, and stacking of the two transparencies reveals the content of the secret. Comparing RGs with basis matrices, one of the major advantages is that the size of generated transparencies is unexpanded. The RG scheme is similar to the probabilistic model of the VC scheme, but the RG scheme is not based on the basis matrices. The recent studies include the RG for colour image [27], and RG schemes [28], [29]. We also compare the proposed method with RG.

In frequency domain, we insert watermark into the coefficients of a transformed image[24] and then watermarked image is inverted to obtain image in spatial domain.[24] The approaches used in frequency domain are JPEGbased[ 25],spread spectrum [26],[27] and content-based approaches [28].Frequency image transformations include the Discrete Fourier Transform (DFT), Discrete Cosine Transform (DCT) and others.

The piracy of software, images, video, audio, and text has long been a concern for owners of these digital assets. Protection schemes are usually based upon the insertion of digital watermarks into the data. The watermarking software introduces small errors into the object being watermarked. These intentional errors are called marks, and all the marks together constitute the watermark. The marks are chosen so as to have an insignificant impact on the usefulness of the data and are placed in such a way that a malicious user cannot destroy them without making the data significantly less useful.

Mobasseri presented the method of a message either encrypted or unencrypted, can be hidden in a computer video file (containing the picture of, for instance, an innocent 2 year old baby) and transmitted over the Internet, a CD or DVD, or any other medium [5].Shiguo lian provide the main goal of steganography is to communicate securely in a completely undetectable manner and to avoid drawing suspicion to the transmission of a hidden data [4]. III. PROPOSED WORK A. Video Compression Video compression uses modern coding techniques to reduce redundancy in video data. Video compression typically operates on square-shaped groups of neighboring pixels, often called macro blocks. These pixel groups or blocks of pixels are compared from one frame to the next and the video compression code sends only the differences within those blocks.