Amitava Nag

A novel technique for image steganography based on Block-DCT and Huffman Encoding

Image steganography is the art of hiding information into a cover image. This paper presents a novel technique for Image steganography based on Block-DCT, where DCT is used to transform original image (cover image) blocks from spatial domain to frequency domain. Firstly a gray level image of size M x N is divided into no joint 8 x 8 blocks and a two dimensional Discrete Cosine Transform (2-d DCT) is performed on each of the P = MN / 64 blocks. Then Huffman encoding is also performed on the secret messages/images before embedding and each bit of Huffman code of secret message/image is embedded in the frequency domain by altering the least significant bit of each of the DCT coefficients of cover image blocks. The experimental results show that the algorithm has a high capacity and a good invisibility. Moreover PSNR of cover image with stego-image shows the better results in comparison with other existing steganography approaches. Furthermore, satisfactory security is maintained since the secret message/image cannot be extracted without knowing decoding rules and Huffman table.

Image encryption using affine transform and XOR operation

Image encryption is a suitable method to protect image data. Image and text data has their unique features. The available encryption algorithms are good for text data. They may not be suitable for multimedia data. In fact the pixels of natural images are highly correlated to their neighboring pixels. Due to this strong correlation any pixel can be practically predicted from the values of its neighbors. In this article, we propose a new location transformation based encryption technique. We redistribute the pixel values to different location using affine transform technique with four 8-bit keys. The transformed image then divided into 2 pixels × 2 pixels blocks and each block is encrypted using XOR operation by four 8-bit keys. The total key size used in our algorithm is 64 bit which proves to be strong enough. The experimental results proved that after the affine transform the correlation between pixel values was significantly decreased.

A Weighted Location Based LSB Image Steganography Technique

Steganography is the art of hiding the presence of communication by embedding secret messages into innocent, innocuous looking cover documents, such as digital images, videos, sound files. We present here a novel steganographic method based on affine cipher encryption algorithm and the least significant bit (LSB) substitution in order to provide a strong security and imperceptible visual quality to secret message. We encrypt the 8 bit secret image by changing pixel values using affine cipher. After that each 8 bit pixel of encrypted secret image is divided into 4 groups of 2 bit each. Each part which have a decimal value between 0 to 3 determines the location in each pixel of cover image where to embed the message. We do not store the actual secret message instead we encode the secret message into cover image using the value of each group of secret message. Since, we have two layers of encoding: one using private keys of affine cipher and other for steganography, our methods proves to be more secure than others. Our experimental results also proves that the proposed method has got an acceptable image quality as supported by PSNR values.

Weather Data Mining using Artificial Neural Network

Weather Data Mining is a form of Data mining concerned with finding hidden patterns inside largely available meteorological data, so that the information retrieved can be transformed into usable knowledge. A variety of data mining tools and techniques are available in the industry, but they have been used in a very limited way for meteorological data. In this paper, a neural network-based algorithm for predicting the atmosphere for a future time and a given location is presented. We have used Back Propagation Neural (BPN) Network for initial modelling. The results obtained by BPN model are fed to a Hopfield Network. The performance of our proposed ANN-based method (BPN and Hopfield Network based combined approach) tested on 3 years weather data set comprising 15000 records containing attributes like temperature, humidity and wind speed. The prediction error is found to be very less and the learning converges very sharply. The main focus of this paper is based on predictive data mining by which we can extract interesting (non-trivial, implicit, previously unknown and potentially useful) patterns or knowledge from huge amount of meteorological data.

A new audio steganography scheme based on location selection with enhanced security

Steganography is the art and science of secret communication. In this paper a new scheme for digital audio steganography is presented where the bits of a secret message are embedded into the coefficients of a cover audio. Each secret bit is embedded into the selected position of a cover coefficient. The position for insertion of a secret bit is selected from the 0th (Least Significant Bit) to 7th LSB based on the upper three MSB (Most Significant Bit). This scheme provides high audio quality, robustness and lossless recovery from the cover Audio.

Secret Image Sharing Scheme Based on a Boolean Operation

Abstract Traditionally extensive researches have been done on secret image sharing which support the fault tolerance property. But their reconstruction complexity is high. Some research papers on secret image sharing are also available with smaller reconstruction complexity, due to the use of a Boolean operation. But these research works lack the fault tolerance property which is the heart of secret sharing. This paper deals with a general (k, n) secret image sharing scheme for gray scale images with both low reconstruction complexity and preservation of the fault tolerance property. Moreover, the proposed sharing generation technique can also be applied on colour images.

Secure Data Outsourcing in the Cloud Using Multi-secret Sharing Scheme (MSSS)

In the last few years, the demand of data outsourcing in the cloud has enormously increased. However, there are some significant barriers to cloud computing adoption. One of the most significant barriers of outsourcing data in the cloud computing is its security issues especially when sensitive data such as personal profile, financial records, medical reports, etc. are outsourced on cloud servers. Therefore, strong security measures are essential to protect data within the cloud. Recently, secret sharing schemes have been applied to protect sensitive data in cloud storage. In this paper, we propose a (t, n) multi secret sharing scheme (MSSS) for secure data outsourcing in the cloud. In the proposed scheme, t secrets are divided into n shares, which are distributed to n cloud servers (one share per server) and a trusted user can recover all secrets by combining shares from at least t servers. The analysis shows that the proposed scheme can provide secure and efficient data outsourcing system in the cloud.

Semi Random Position Based Steganography for Resisting Statistical Steganalysis

Steganography is the branch of information hiding for secret communication. The simplest and widely used steganography is the LSB based approach due to its visual quality with high embedding capacity. However, LSB based steganography techniques are not secure against statistical steganalysis mainly χ2 attack and Regular Singular (RS) attack. These two staganalysis can easily estimate the hidden message length. This work propose a LSB based steganography technique where first a location is obtained randomly based on the bit pattern (except LSB) of a cover pixel using linear probing and embed a secret bit into LSB. This technique makes the stego-image completely secure against both χ2 attack and RS attack.

Location-Based Image Steganography

The objective of steganography is to conceal the presence of a secret communication. Nevertheless, with the development of steganalytic attack, also known as steganalysis, there are many statistical methods to estimate the presence and ratio of secret messages. The chi square (χ2) attack and regular-singular (RS) attack are two well recognized and widely applied statistical steganalysis schemes. In this paper, a new image steganography scheme with location selection is proposed to resist statistical steganalysis. The experiment results indicate that the proposed method can resist both χ2 attacks as well as RS attacks.

A Huffman Code Based Image Steganography Technique

We present here a novel steganographic method based on Huffman coding and the least significant bit substitution in order to provide high embedding capacity, a strong security and imperceptible visual quality to secret message. Every eight bits of the secret image are first encoded by building a Huffman tree. After that those encoded bits of secret image are divided into 4 groups. Each part has a decimal value between 0 to 3. These decimal values determine the location where to embed the message in a particular pixel of cover image. To embed the message we just put a one in the corresponding location in a pixel of the cover image which identified by the decimal values of the secret image. Since Huffman Table reduces the size of the original image, an attacker cannot easily recover from the stego image those fine details of the original image that would enable him to mount a reliable attack. We have got comparable visual quality as the Peak Signal to Noise Ratio values lie between 30 dB to 31 dB.