A New Approach for Video Steganography Based on Randomization and Parallelization

Steganography is considered as a useful approach for hiding data in a carrier file; data could be any multimedia file such as image, text, audio, video. Steganography is referred to as the science of invisible communication. Sometimes steganography is used with encryption schemes of cryptography to provide additional security for the secret data. A good steganographic technique must fulfill three basic requirements of steganography, i.e., capacity, imperceptibility, and robustness. Videos have become a very popular choice for steganography due to its significant growth on Internet and are able to fulfill all these requirements due to its large size and statistical complexity. This paper presents the survey of video steganography schemes based on spatial domain techniques.

Video Steganography Techniques in Spatial Domain—A Survey

In the last few decades, information security has gained huge importance owing to the massive growth in digital communication; hence, driving steganography to the forefront for secure communication Steganography is a practice of concealing information or message in covert communication which involves hiding the information in any multimedia file such as text, image, or video Many contributions have been made in the domain of image steganography; however, due to the low embedding capacity and robustness of images; videos are gaining more attention of academic researchers This paper aims to provide a qualitative as well as quantitative analysis of various video steganography techniques by highlighting their properties, challenges, pros, and cons Moreover, different quality metrics for the evaluation of distinct steganography techniques have also been discussed The paper also provides an overview of steganalysis attacks which are commonly employed to test the security of the steganography techniques The experimental analysis of some of the prominent techniques using different quality metrics has also been done This paper also presented a critical analysis driven from the literature and the experimental results The primary objective of this paper is to help the beginners to understand the basic concepts of this research domain to initiate their research in this field Further, the paper highlighted the real-life applications of video steganography and also suggested some future directions which require the attention of the research community

A survey on information hiding using video steganography

To maintain the secrecy of information, various information hiding techniques are used. Steganography is one of them, which means hide information inside another digital media like text, image, audio, video etc. without being detected by human visual system (HVS). Recently Video steganography has become a strong tool to hide large amount of data rather than image steganography. This paper is proposing an idea about a hybrid approach for video steganography to achieve high capacity data & high quality of stego video on the basis of quality metrics like PSNR, MSE and BER. The proposed methodology is a combo pack of various techniques such as RSA encryption, Edge detection, Identical Match and 4LSB substitution, in which a video file will be used to hide text message inside in all layers of RGB color frames of video. The experimental results are analyzed on MATLAB software on cover video of ‘rhinos’ and text secret message is embedding inside the video. The resulting values show that our proposed algorithm has high imperceptibility and security and resists the visual attacks.

A hybrid approach for video steganography using edge detection and identical match techniques

Steganography has been a great interest since long time ago. There are a lot of methods that have been widely used since long past. Recently, there has been a growing interest in the use of sparse representation in signal processing. Sparse representation can efficiently model signals in different applications to facilitate processing. Much of the previous work was focused on image and audio sparse representation for steganography. In this paper, a new steganography scheme based on video sparse representation (VSR) is proposed. To exploit proper dictionary, KSVD algorithm is applied to DCT coefficients of Y component related to video (cover) frames. Both I and Q components of video frames are used for secure message insertion. The aim is to hide secret messages into non-zero coefficients of sparse representation of DCT called, I and Q video frames. Several experiments are performed to evaluate the performance of the proposed algorithm, in case of some metrics such as pick signal to noise ratio (PSNR), the hiding ratio (HR), bit error rate (BER) and similarity (Sim) of secret message, and also runtime. The simulation results show that the proposed method exhibits appropriate invisibility and robustness.

A new steganography algorithm based on video sparse representation

Need of hiding information from intruders has been around since ancient times. Nowadays Digital media is getting advanced like text, image, audio, video etc. To maintain the secrecy of information, different methods of hiding have been evolved. One of them is Steganography, which means hiding information under some other information without noticeable change in cover information. Recently Video Steganography has become a boon for providing large amount of data to be transferred secretly. Video is simply a sequence of images, hence much space is available in between for hiding information. In proposed scheme video steganography is used to hide a secret video stream in cover video stream. Each frame of secret video will be broken into individual components then converted into 8-bit binary values, and encrypted using XOR with secret key and encrypted frames will be hidden in the least significant bit of each frames using sequential encoding of Cover video. To enhance more security each bit of secret frames will be stored in cover frames following a pattern BGRRGBGR.

A secure video steganography with encryption based on LSB technique

EfficientNet convolutional neural networks-based Android malware detection

HFBO-KSELM: Hybrid Flash Butterfly Optimization-based Kernel Softplus Extreme Learning Machine for Classification of Chronic Kidney Disease

Image classification is one of the computer vision problems. It is a supervised learning technique, in this, images are classified according to their different characteristics (features). There are various facial image datasets of different persons with different facial expressions. Classification based on different facial expressions is always a challenging task for researchers because a person can have different facial expressions like smiling, sad, normal, with or without goggles, etc., depending upon the mood of the person. Deep learning technique like Convolutional neural networks (CNN) is an indemand technique to classify images based on their features. This paper demonstrates the performance of CNN using a different number of images with different numbers of expressions per person and keeping all the other parameters the same. For performance measurement of CNN, the faces94 dataset of is used. Based on the evaluated results, some important points are highlighted.

Pooja Yadav

Papers

A secure video steganography with encryption based on LSB technique

EfficientNet convolutional neural networks-based Android malware detection

HFBO-KSELM: Hybrid Flash Butterfly Optimization-based Kernel Softplus Extreme Learning Machine for Classification of Chronic Kidney Disease

Performance of CNN for different facial expression images with varying input dataset sizes