49 research outputs found

    Video Steganography Techniques: A Survey

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    In digital world, information security is the major issue in digital communication on a network from the third party hackers. Steganography techniques play an important role in information security. These are the secure techniques, used for concealing existence of secret information in any digital cover object viz. image, audio, video files. In last several decades, significant researches have been done on video and image steganography techniques because data embedding and data extraction is very simple. However, many researchers also take the audio file as a cover object where robustness and undetectability of information is very difficult task. The main objective of steganography is hiding the existence of the embedded data in any digital cover object. Steganography technique must be robust against the various image-processing attacks. Nowadays, video files are more accepted because of large size and memory requirements. This paper intends to provide a survey on video techniques and provide the fundamental concept of the steganography and their uses

    Performance evaluation measurement of image steganography techniques with analysis of LSB based on variation image formats

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    Recently, Steganography is an outstanding research area which used for data protection from unauthorized access. Steganography is defined as the art and science of covert information in plain sight in various media sources such as text, images, audio, video, network channel etc. so, as to not stimulate any suspicion; while steganalysis is the science of attacking the steganographic system to reveal the secret message. This research clarifies the diverse showing the evaluation factors based on image steganographic algorithms. The effectiveness of a steganographic is rated to three main parameters, payload capacity, image quality measure and security measure. This study is focused on image steganographic which is most popular in in steganographic branches. Generally, the Least significant bit is major efficient approach utilized to embed the secret message. In addition, this paper has more detail knowledge based on Least significant bit LSB within various Images formats. All metrics are illustrated in this study with arithmetical equations while some important trends are discussed also at the end of the paper

    Hiding Data in Image using Extended Pixel Mapping Method

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    — Internet technologies are currently charring an important role in our day to day life. It has the benefit as well as disadvantages also.This in term generates the needs of data activity technology for maintaining the secrecy of the key information. The steganograpic concept of data hiding is used in this method. The method used spatial domain technique. This algorithm used image as a carrier medium for hiding the data. In this pixel component are used for hiding the data. For achieving this pixel index value and their position are calculated. According to this key will be generated and by using key data is hided.Experimental result shows that the perceptual quality of hided image is high in this technique. The key idea of this project is to hide the data in carrier image and retrieve data from carrier image without affecting without affecting the perceptual transparency of the data hided image. This system provides compression of data so that payload capacity of the system will be increases. DOI: 10.17762/ijritcc2321-8169.150512

    An enhanced method based on intermediate significant bit technique for watermark images

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    Intermediate Significant Bit digital watermarking technique (ISB) is a new approved technique of embedding a watermark by replacing the original image pixels with new pixels. This is done by ensuring a close connection between the new pixels and the original, and at the same time, the watermark data can be protected against possible damage. One of the most popular methods used in watermarking is the Least Significant Bit (LSB). It uses a spatial domain that includes the insertion of the watermark in the LSB of the image. The problem with this method is it is not resilient to common damage, and there is the possibility of image distortion after embedding a watermark. LSB may be used through replacing one bit, two bits, or three bits; this is done by changing the specific bits without any change in the other bits in the pixel. The objective of this thesis is to formulate new algorithms for digital image watermarking with enhanced image quality and robustness by embedding two bits of watermark data into each pixel of the original image based on ISB technique. However, to understand the opposite relationship between the image quality and robustness, a tradeoff between them has been done to create a balance and to acquire the best position for the two embedding bits. Dual Intermediate Significant Bits (DISB) technique has been proposed to solve the existing LSB problem. Trial results obtained from this technique are better compared with the LSB based on the Peak Signal to Noise Ratio (PSNR) and Normalized Cross Correlation (NCC). The work in this study also contributes new mathematical equations that can study the change on the other six bits in the pixel after embedding two bits

    Pixel value differencing steganography techniques: Analysis and open challenge

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    Steganography is the science of secret data communication using carrier medium, such as images, videos, text, and networks. Image steganography is majorly divided into spatial and frequency domains. Pixel value differencing (PVD) considered as good steganographic algorithm due to its high payload and good visual perception in spatial domain. The purpose of this paper is two folded. First is the critical analysis of current PVD methods using evaluating parameters (payload, visual quality and resistance of attacks) and secondly it highlights the current promising directions on PVD steganographic research

    Ant colony optimization (ACO) based data hiding in image complex region

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    This paper presents data an Ant colony optimization (ACO) based data hiding technique. ACO is used to detect complex region of cover image and afterward, least significant bits (LSB) substitution is used to hide secret information in the detected complex regions’ pixels. ACO is an algorithm developed inspired by the inborn manners of ant species. The ant leaves pheromone on the ground for searching food and provisions. The proposed ACO-based data hiding in complex region establishes an array of pheromone, also called pheromone matrix, which represents the complex region in sequence at each pixel position of the cover image. The pheromone matrix is developed according to the movements of ants, determined by local differences of the image element’s intensity. The least significant bits of complex region pixels are substituted with message bits, in order to hide secret information. The experimental results, provided, show the significance of the performance of the proposed method

    Multi-Stage Protection Using Pixel Selection Technique for Enhancing Steganography

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    Steganography and data security are extremely important for all organizations. This research introduces a novel stenographic method called multi-stage protection using the pixel selection technique (MPPST). MPPST is developed based on the features of the pixel and analysis technique to extract the pixel's characteristics and distribution of cover-image. A pixel selection technique is proposed for hiding secret messages using the feature selection method. The secret file is distributed and embedded randomly into the stego-image to make the process of the steganalysis complicated.  The attackers not only need to deter which pixel values have been selected to carry the secret file, they also must rearrange the correct sequence of pixels. MPPST generates a complex key that indicates where the encrypted elements of the binary sequence of a secret file are. The analysis stage undergoes four stages, which are the calculation of the peak signal-to-noise ratio, mean squared error, histogram analysis, and relative entropy. These four stages are used to demonstrate the characteristics of the cover image. To evaluate the proposed method, MPPST is compared to the standard technique of Least Significant Bit (LSB) and other algorithms from the literature. The experimental results show that MPPST outperforms other algorithms for all instances and achieves a significant security enhancement

    Ant Colony Optimization (ACO) based Data Hiding in Image Complex Region

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    This paper presents data an Ant colony optimization (ACO) based data hiding technique. ACO is used to detect complex region of cover image and afterward, least significant bits (LSB) substitution is used to hide secret information in the detected complex regions’ pixels. ACO is an algorithm developed inspired by the inborn manners of ant species. The ant leaves pheromone on the ground for searching food and provisions. The proposed ACO-based data hiding in complex region establishes an array of pheromone, also called pheromone matrix, which represents the complex region in sequence at each pixel position of the cover image. The pheromone matrix is developed according to the movements of ants, determined by local differences of the image element’s intensity. The least significant bits of complex region pixels are substituted with message bits, to hide secret information. The experimental results, provided, show the significance of the performance of the proposed method

    Optimization of medical image steganography using n-decomposition genetic algorithm

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    Protecting patients' confidential information is a critical concern in medical image steganography. The Least Significant Bits (LSB) technique has been widely used for secure communication. However, it is susceptible to imperceptibility and security risks due to the direct manipulation of pixels, and ASCII patterns present limitations. Consequently, sensitive medical information is subject to loss or alteration. Despite attempts to optimize LSB, these issues persist due to (1) the formulation of the optimization suffering from non-valid implicit constraints, causing inflexibility in reaching optimal embedding, (2) lacking convergence in the searching process, where the message length significantly affects the size of the solution space, and (3) issues of application customizability where different data require more flexibility in controlling the embedding process. To overcome these limitations, this study proposes a technique known as an n-decomposition genetic algorithm. This algorithm uses a variable-length search to identify the best location to embed the secret message by incorporating constraints to avoid local minimum traps. The methodology consists of five main phases: (1) initial investigation, (2) formulating an embedding scheme, (3) constructing a decomposition scheme, (4) integrating the schemes' design into the proposed technique, and (5) evaluating the proposed technique's performance based on parameters using medical datasets from kaggle.com. The proposed technique showed resistance to statistical analysis evaluated using Reversible Statistical (RS) analysis and histogram. It also demonstrated its superiority in imperceptibility and security measured by MSE and PSNR to Chest and Retina datasets (0.0557, 0.0550) and (60.6696, 60.7287), respectively. Still, compared to the results obtained by the proposed technique, the benchmark outperforms the Brain dataset due to the homogeneous nature of the images and the extensive black background. This research has contributed to genetic-based decomposition in medical image steganography and provides a technique that offers improved security without compromising efficiency and convergence. However, further validation is required to determine its effectiveness in real-world applications
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