V. Hima Deepthi

Bio: V. Hima Deepthi is an academic researcher. The author has contributed to research in topics: Wavelet & Steganography. The author has an hindex of 3, co-authored 4 publications receiving 38 citations.

A sparse representation based image steganography using Particle Swarm Optimization and wavelet transform

Abstract: With the growth of information technology, information security is a major concern in the interactive environment, where there is no security for the messages send to and from the receiver. A technology named image steganography has been employed that ensures security to the covert communication and safeguarding the information. Image steganography hides the secret message in any of the recipient images and sends the secret message such that the message is visible only to the sender and the receiver. This paper proposes a method for image steganography using sparse representation, and an algorithm named Particle Swarm Optimization (PSO) algorithm for effective selection of the pixels for the purpose of embedding the secret audio signal in the image. PSO-based pixel selection procedure uses a fitness function that depends on the cost function. Cost function calculates the edge, entropy, and intensity of the pixel for evaluating fitness. Simulation has been done and comparison of the PSO with the other existing methods in terms of Peak-Signal-to-Noise-Ratio (PSNR) and Mean Square Error (MSE) determines the proposed PSO, as an effective method. The proposed method achieved a better PSNR and MSE values of 47.6 dB and 0.75 respectively.

A Multiple Criteria-Based Cost Function Using Wavelet and Edge Transformation for Medical Image Steganography

Abstract: Abstract With the ever-increasing need for concealing messages within cover media like image, video, and audio, numerous attempts have been developed for steganography. Most of the steganographic techniques perform their embedding operation on the cover image without selecting a better location. The right selection of location for embedding the information can lead to high imperceptibility and robustness. Accordingly, in this paper, we develop a new cost function for estimating the cost of every pixel to identify the good location to embed the message data. The proposed cost estimation procedure utilizes multiple parameters like wavelet coefficient, edge transformation, and pixel intensity. The proposed cost matrix is then utilized to embed the message data into the cover media using an embedding integer. The proposed steganographic technique is experimented with two magnetic resonance brain images, and the results are analyzed with the peak-to-peak signal-to-noise ratio (PSNR) and mean square error. The robustness analysis ensured that the proposed steganographic technique outperforms the existing methods by reaching the maximum PSNR of 72.74 dB.

Wavelet transform-based steganographic method for secure data communication using OFDM system

Abstract: Purpose Fueled by the rapid growth of internet, steganography has emerged as one of the promising techniques in the communication system to obscure the data. Steganography is defined as the process of concealing the data or message within media files without affecting the perception of the image. Media files, like audio, video, image, etc., are utilized to embed the message. Nowadays, steganography is also used to transmit the medical information or diagnostic reports. The paper aims to discuss these issues. Design/methodology/approach In this paper, the novel wavelet transform-based steganographic method is proposed for secure data communication using OFDM system. The embedding and extraction process in the proposed steganography method exploits the wavelet transform. Initially, the cost matrix is estimated by the following three aspects: pixel intensity, edge transformation and wavelet transform. The cost estimation matrix provides the location of the cover image where the message is to be entrenched. Then, the wavelet transform is utilized to embed the message into the cover image according to the cost value. Subsequently, in the extraction process, the wavelet transform is applied to the embedded image to retrieve the message efficiently. Finally, in order to transfer the secret information over the channel, the newly developed wavelet-based steganographic method is employed for the OFDM system. Findings The experimental results are evaluated and performance is analyzed using PSNR and MSE parameters and then compared with existing systems. Thus, the outcome of our wavelet transform steganographic method achieves the PSNR of 71.5 dB which ensures the high imperceptibility of the image. Then, the outcome of the OFDM-based proposed steganographic method attains the higher PSNR of 71.07 dB that proves the confidentiality of the message. Originality/value In the authors’ previous work, the embedding and extraction process was done based on the cost estimation matrix. To enhance the security throughout the communication system, the novel wavelet-based embedding and extraction process is applied to the OFDM system in this paper. The idea behind this method is to attain a higher imperceptibility and robustness of the image.

Entropy based cost function for wavelet based medical image steganography

Abstract: Security is the rising concern in this technical revolution that is looming the researchers towards new contribution. The major contribution is the development of the steganography that provides security to the secret messages through hiding them in the cover media, which is the image, video, or an audio. Image steganography uses image as a cover media to carry the secret message with a high degree of security. This paper proposes a method of hiding the text message in the image for which a Discrete Wavelet Transform (DWT) is employed with the cost function that locates a position to undergo embedding. The cost function uses entropy, intensity, and the edge of the image to calculate the position of embedding. Experimentation has been done with the MRI brain image as a cover image and the performance analysis in terms of PSNR and Correlation gets evaluated. The comparison of the experimental results of the DB1wavelet with cost function, Haar wavelet, Haar wavelet with cost function, and DB1 wavelet prove that the Haar wavelet with cost function achieves a better PSNR of 43.5200db and a correlation of 96% when compared with the other methods.

An application of preservation technology in inventory control system with price dependent demand and partial backlogging

Abstract: Preservation of a product is an important issue in the inventory control system. It prevents the deterioration effect of the products while these are stored in the warehouse/showroom. Considering deterioration effect of the product and preservation technology, an inventory model of non-instantaneous deteriorating items is developed with the demand dependent on the selling price of the product. Two different preservation rates are considered. Shortages are allowed partially with two different backlogging rates. Due to consideration of three-parameter Weibull distributed deterioration and preservation facility, the corresponding optimization problems are highly nonlinear. So, these problems cannot be solved analytically due to nonlinearity. To overcome this situation, different variants of quantum-behaved particle swarm optimization (QPSO) are used. To illustrate and validate the proposed model, a numerical example is considered and solved for each case, and compared the results with the different variants of QPSO algorithms. Finally, a sensitivity analysis is performed to study the effect of changes of different parameters of the model on the optimal policy.

SSII: Secured and High-Quality Steganography Using Intelligent Hybrid Optimization Algorithms for IoT

Abstract: Internet of Things (IoT) is a domain where the transfer of big data is taking place every single second. The security of these data is a challenging task; however, security challenges can be mitigated with cryptography and steganography techniques. These techniques are crucial when dealing with user authentication and data privacy. In the proposed work, a highly secured technique is proposed using IoT protocol and steganography. This work proposes an image steganography procedure by utilizing the combination of various algorithms that build the security of the secret data by utilizing Binary bit-plane decomposition (BBPD) based image encryption technique. Thereafter a Salp Swarm Optimization Algorithm (SSOA) based adaptive embedding process is proposed to increase the payload capacity by setting different parameters in the steganographic embedding function for edge and smooth blocks. Here the SSOA algorithm is used to localize the edge and smooth blocks efficiently. Then, the hybrid Fuzzy Neural Network with a backpropagation learning algorithm is used to enhance the quality of the stego images. Then these stego images are transferred to the destination in the highly secured protocol of IoT. The proposed steganography technique shows better results in terms of security, image quality, and payload capacity in comparison with the existing state of art methods.

Video Steganography Using Knight Tour Algorithm and LSB Method for Encrypted Data

Abstract: Abstract This paper aims to propose a method for data hiding in video by utilizing the least significant bit (LSB) method and improving it by utilizing the knight tour algorithm for concealing the data inside the AVI video file and using a key function encryption method for encrypting the secret message. First, the secret message is encrypted by utilizing a mathematical equation. The key used in the equation is a set of random numbers. These numbers differ in each implementation to warrant the safety of the hidden message and to increase the security of the secret message. Then, the cover video was converted from a set of frames into separated images to take the advantage of the large size of video file. Afterward, the knight tour algorithm is utilized for random selecting of the pixels inside the frame utilized for embedding the secret message inside it to overcome the shortcoming of the conventional LSB method that utilized the serial selection of pixel and to increase the robustness and security of the proposed method. Afterward, the encrypted secret message is embedded inside the selected pixels by utilizing the LSB method in bits (7 and 8). The observational results have drawn that the proposed method has a superior performance compared to the previous steganography method in terms of quality by a high PSNR of 67.3638 dB and the lowest MSE of 0.2578. Furthermore, this method preserves the security where the secret message cannot be drawn out without knowing the decoding rules.