The smart steganography system using AES & SPK algorithms

In this paper a new steganography approach proposed based on LSB technique by using Alpha channel on JPG cover images and Bit-slicing decomposition and Advanced Encryption Standard (AES) on the secrete image. For this method first the secrete image decomposed to bit streams and the data encrypted using AES algorithm. On the cover side, an alpha channel is attached to the cover image and the data embedded into LSBs of RGBA channels. The method was implemented and tested by using MATLAB® (R2011a)

Conditional Entrench Spatial Domain Steganography

Steganography is a technique of concealing the secret information in a digital carrier media, so that only the authorized recipient can detect the presence of secret information. In this paper, we propose a spatial domain steganography method for embedding secret information on conditional basis using 1-Bit of Most Significant Bit (MSB). The cover image is decomposed into blocks of 8*8 matrix size. The first block of cover image is embedded with 8 bits of upper bound and lower bound values required for retrieving payload at the destination. The mean of median values and difference between consecutive pixels of each 8*8 block of cover image is determined to embed payload in 3 bits of Least Significant Bit (LSB) and 1 bit of MSB based on prefixed conditions. It is observed that the capacity and security is improved compared to the existing methods with reasonable PSNR

Embedding information in DCT coefficients based on average covariance

Embedding information in DCT coefficients based on average covarianc

Robust Lossless Semi Fragile Information Protection in Images

Internet security finds it difficult to keep the information secure and to maintain the integrity of the data. Sending messages over the internet secretly is one of the major tasks as it is widely used for passing the message. In order to achieve security there must be some mechanism to protect the data against unauthorized access. A lossless data hiding scheme is proposed in this paper which has a higher embedding capacity than other schemes. Unlike other schemes that are used for embedding fixed amount of data, the proposed data hiding method is block based approach and it uses a variable data embedding in different blocks which reduces the chances of distortion and increases the hiding capacity of the image. When the data is recovered the original image can be restored without any distortion. Our experimental results indicate that the proposed solution can significantly support the data hiding problem. We achieved good Peak signal-to-noise ratio (PSNR) while hiding large amount of data into smoother regions

Robust image adaptive steganography using integer wavelets

Information-Theoretic Analysis for Parallel Gaussian Models of Images prescribe embedding the secret data in low and mid frequency regions of image which have large energies. In this paper, we propose a novel steganographic scheme called Robust Image Adaptive Steganography using Integer Wavelet Transform(RIASlWT), which is a practical realization of these prescriptions. Using this scheme we can hide large volumes of data without causing any perceptual degradation of the cover image. The scheme embeds the payload in every non-overlapping 4x4 blocks of the low frequency band of cover image, two pixels at a time, one on either sides of the principal diagonal. Tests for the similarity between the Condition Number of the cover image and the stego image are done for further embedding. We also perform cover image adjustment before embedding the payload in order to ensure lossless recovery. Embedding done in the low frequency bands ensures robustness against attacks such as compression and filtering. Experimental results show better trade off between Visual perceptivity and capacity compared to the existing algorithms

Международная конференция студентов и молодых ученых «Весенние дни науки» : сборник докладов (Екатеринбург, 22 – 24 апреля 2021 г.)

В сборник вошли материалы докладов, представленных на тематических секциях международной конференции студентов и молодых ученых «Весенние дни науки», которая состоялась в Екатеринбурге 22 – 24 апреля 2021 г. Организаторы конференции: Институт экономики и управления УрФУ. Сборник подготовлен Институтом экономики и управления Уральского федерального университета имени первого Президента России Б.Н. Ельцина. Адресован исследователям, студентам, магистрантам и аспирантам