Information Hiding in Images Using Steganography Techniques

Innovation of technology and having fast Internet make information to distribute over the world easily and economically. This is made people to worry about their privacy and works. Steganography is a technique that prevents unauthorized users to have access to the important data. The steganography and digital watermarking provide methods that users can hide and mix their information within other information that make them difficult to recognize by attackers. In this paper, we review some techniques of steganography and digital watermarking in both spatial and frequency domains. Also we explain types of host documents and we focused on types of images

Analysis of Routing Protocols over VANET

Vehicular Ad-hoc Network (VANET) is a new network technology where the cars are used as mobile nodes to form a communication network. In VANET, routing protocols have a significant role in terms of the performance because they determine the way of sending and receiving packets between mobile nodes. In this paper, we examine and analyze the performance of Ad-hoc On-Demand (AODV), Ad-hoc On-demand Multipath Distance Vector (AOMDV), Dynamic Source Routing (DSR) and Destination-Sequenced Distance Vector (DSDV) routing protocols over two different traffic connections; TCP and Constant Bit Rate (CBR) using different speeds and packet sizes. The performance measurements; Packet Delivery Ratio, Average End to End Delay and Average Throughput are examined with respect to speed and packet size. The objective of this study is to find the best routing protocol over all circumstances. Based on our validated results, DSR performs the best among all evaluated protocols

Efficient And Robust Video Steganography Algorithms For Secure Data Communication

Nowadays, the science of information hiding has gained tremendous significance due to advances in information and communication technology. The performance of any steganography method relies on the imperceptibility, embedding capacity, and robustness against attacks. This research provides solutions for the existing video steganography problems by proposing new and effective methods for digital video steganography. The key objectives of our paper are as follows: 1) a highly secure video steganography algorithm based on error correcting codes (ECC); 2) an increased payload video steganography algorithm in the discrete wavelet domain based on ECC; 3) a novel video steganography algorithm based on Kanade-Lucas-Tomasi (KLT) tracking and ECC; 4) a robust video steganography algorithm in the wavelet domain based on KLT tracking and ECC; and 5) a video steganography algorithm based on multiple object tracking and ECC. The experimental results from our research demonstrate that our proposed algorithms achieve higher embedding capacity as well as better imperceptibility of stego videos. Furthermore, the preprocessing stages increase the security and robustness of the proposed algorithms against attacks when compared to state-of-the-art steganographic methods

An Efficient Video Steganography Algorithm Based on BCH Codes

© ASEE 2015In this paper, in order to improve the security and efficiency of the steganography algorithm, we propose an efficient video steganography algorithm based on the binary BCH codes. First the pixels’ positions of the video frames’ components are randomly permuted by using a private key. Moreover, the bits’ positions of the secret message are also permuted using the same private key. Then, the secret message is encoded by applying BCH codes (n, k, t), and XORed with random numbers before the embedding process in order to protect the message from being read. The selected embedding area in each Y, U, and V frame components is randomly chosen, and will differ from frame to frame. The embedding process is achieved by hiding each of the encoded blocks into the 3-2-2 least significant bit (LSB) of the selected YUV pixels. Experimental results have demonstrated that the proposed algorithm have a high embedding efficiency, high embedding payload, and resistant against hackers

Efficient and Robust Video Steganography Algorithms for Secure Data Communication

Over the last two decades, the science of secretly embedding and communicating data has gained tremendous significance due to the technological advancement in communication and digital content. Steganography is the art of concealing secret data in a particular interactive media transporter such as text, audio, image, and video data in order to build a covert communication between authorized parties. Nowadays, video steganography techniques are important in many video-sharing and social networking applications such as Livestreaming, YouTube, Twitter, and Facebook because of noteworthy developments in advanced video over the Internet. The performance of any steganography method, ultimately, relies on the imperceptibility, hiding capacity, and robustness against attacks. Although many video steganography methods exist, several of them lack the preprocessing stages. In addition, less security, low embedding capacity, less imperceptibility, and less robustness against attacks are other issues that affect these algorithms. This dissertation investigates and analyzes cutting edge video steganography techniques in both compressed and raw domains. Moreover, it provides solutions for the aforementioned problems by proposing new and effective methods for digital video steganography. The key objectives of this research are to develop: 1) a highly secure video steganography algorithm based on error correcting codes (ECC); 2) an increased payload video steganography algorithm in the discrete wavelet domain based on ECC; 3) a novel video steganography algorithm based on Kanade-Lucas-Tomasi (KLT) tracking and ECC; 4) a robust video steganography algorithm in the wavelet domain based on KLT tracking and ECC; 5) a new video steganography algorithm based on the multiple object tracking (MOT) and ECC; and 6) a robust and secure video steganography algorithm in the discrete wavelet and discrete cosine transformations based on MOT and ECC. The experimental results from our research demonstrate that our proposed algorithms achieve higher embedding capacity as well as better imperceptibility of stego videos. Furthermore, the preprocessing stages increase the security and robustness of the proposed algorithms against attacks when compared to state-of-the-art steganographic methods

A Highly Secure Video Steganography using Hamming Code (7, 4)

Due to the high speed of internet and advances in technology, people are becoming more worried about information being hacked by attackers. Recently, many algorithms of steganography and data hiding have been proposed. Steganography is a process of embedding the secret information inside the host medium (text, audio, image and video). Concurrently, many of the powerful steganographic analysis software programs have been provided to unauthorized users to retrieve the valuable secret information that was embedded in the carrier files. Some steganography algorithms can be easily detected by steganalytical detectors because of the lack of security and embedding efficiency. In this paper, we propose a secure video steganography algorithm based on the principle of linear block code. Nine uncompressed video sequences are used as cover data and a binary image logo as a secret message. The pixels’ positions of both cover videos and a secret message are randomly reordered by using a private key to improve the system’s security. Then the secret message is encoded by applying Hamming code (7, 4) before the embedding process to make the message even more secure. The result of the encoded message will be added to random generated values by using XOR function. After these steps that make the message secure enough, it will be ready to be embedded into the cover video frames. In addition, the embedding area in each frame is randomly selected and it will be different from other frames to improve the steganography scheme’s robustness. Furthermore, the algorithm has high embedding efficiency as demonstrated by the experimental results that we have obtained. Regarding the system’s quality, the Pick Signal to Noise Ratio (PSNR) of stego videos are above 51 dB, which is close to the original video quality. The embedding payload is also acceptable, where in each video frame we can embed 16 Kbits and it can go up to 90 Kbits without noticeable degrading of the stego video’s quality

A Robust and Secure Video Steganography Method in DWT-DCT Domains Based on Multiple Object Tracking and ECC

Over the past few decades, the art of secretly embedding and communicating digital data has gained enormous attention because of the technological development in both digital contents and communication. The imperceptibility, hiding capacity, and robustness against attacks are three main requirements that any video steganography method should take into consideration. In this paper, a robust and secure video steganographic algorithm in discrete wavelet transform (DWT) and discrete cosine transform (DCT) domains based on the multiple object tracking (MOT) algorithm and error correcting codes is proposed. The secret message is preprocessed by applying both Hamming and Bose, Chaudhuri, and Hocquenghem codes for encoding the secret data. First, motion-based MOT algorithm is implemented on host videos to distinguish the regions of interest in the moving objects. Then, the data hiding process is performed by concealing the secret message into the DWT and DCT coefficients of all motion regions in the video depending on foreground masks. Our experimental results illustrate that the suggested algorithm not only improves the embedding capacity and imperceptibility but also enhances its security and robustness by encoding the secret message and withstanding against various attacks

Image steganography based on DNA sequence translation properties

Digital communication has become a vital part of daily life nowadays, many applications are using internet-based communication and here the importance of security rose to have a secure communication between two parties to prevent authorized access to sensitive data. These requirements led to a number of research in information security that has been done in the past two decades. Cryptography and steganography are the two main methods that are being used for information security. Cryptography refers to techniques that encrypt a message to be sent to a destination using different methods to be done. On the other hand, steganography is the science of hiding information from others using another cover message or media such as image, audio, video, and DNA sequence. This paper proposed a new method to hide information in an image using the least significant bit (LSB) based on Deoxyribonucleic Acid (DNA) sequence. To accomplish this, the proposed scheme used properties of DNA sequence when codons that consist of three nucleotides are translated to proteins. The LSB of two pixels from the image are taken to represent a codon and then translate them to protein. The secret message bits are injected into codons before the translation process which slightly distorts the image and makes the image less suspicious and hard to detect the hidden message. The experimental results indicate the effeteness of the proposed method

A Highly Secure Quantum Communication Scheme for Blind Signature using Qubits and Qutrits

© ASEE 2014The advances in hardware speed has being rapidly increased rapidly in the recent years, which will lead to the ability to decrypt well known decryption algorithms in short time. This motivated many researchers to investigate better techniques to prevent disclosing and eavesdropping of communicated data. Quantum Cryptography is a promising solution, since it relies on the prosperities of quantum physics that ensure no change in the quantum state without the knowledge of the sender/receiver. Quantum Communication Scheme for Blind Signature with Two-Particle Entangled Quantum-Trits was proposed by Jinjing et al. [1] That scheme uses qutits during the communications and the process of the encryption is not clearly defined. In this paper we suggest a modification of Jinjing et al. protocol using qubits and qutrits during the encryption and decryption which proposed by Zhou et al. [2] The proposed algorithms enhances the efficiency of that scheme and creates a quantum cryptosystem environment to exchange the data in a secure way. During the communications, all the messages are encrypted using the the private key of the sender and a third party verifies the authenticity and the blindness of the signature

A Comprehensive Survey on Bone Segmentation Techniques in Knee Osteoarthritis Research: From Conventional Methods to Deep Learning

Knee osteoarthritis (KOA) is a degenerative joint disease, which significantly affects middle-aged and elderly people. The majority of KOA is primarily based on hyaline cartilage change, according to medical images. However, technical bottlenecks such as noise, artifacts, and modality pose enormous challenges for an objective and efficient early diagnosis. Therefore, the correct prediction of arthritis is an essential step for effective diagnosis and the prevention of acute arthritis, where early diagnosis and treatment can assist to reduce the progression of KOA. However, predicting the development of KOA is a difficult and urgent problem that, if addressed, could accelerate the development of disease-modifying drugs, in turn helping to avoid millions of total joint replacement procedures each year. In knee joint research and clinical practice there are segmentation approaches that play a significant role in KOA diagnosis and categorization. In this paper, we seek to give an in-depth understanding of a wide range of the most recent methodologies for knee articular bone segmentation; segmentation methods allow the estimation of articular cartilage loss rate, which is utilized in clinical practice for assessing the disease progression and morphological change, ranging from traditional techniques to deep learning (DL)-based techniques. Moreover, the purpose of this work is to give researchers a general review of the currently available methodologies in the area. Therefore, it will help researchers who want to conduct research in the field of KOA, as well as highlight deficiencies and potential considerations in application in clinical practice. Finally, we highlight the diagnostic value of deep learning for future computer-aided diagnostic applications to complete this review