A Review on the Recent Trends of Image Steganography for VANET Applications

Image steganography is a technique of concealing confidential information within an image without dramatically changing its outside look.Whereas vehicular ad hoc networks(VANETs),which enable vehicles to communicate with one another and with roadside infrastructure to enhance safety and traffic flow provide a range of value-added services,as they are an essential component of modern smart transportation systems.VANETs steganography has been suggested by many authors for secure,reliable message transfer between terminal/hope to terminal/hope and also to secure it from attack for privacy protection.This paper aims to determine whether using steganography is possible to improve data security and secrecy in VANET applications and to analyze effective steganography techniques for incorporating data into images while minimizing visual quality loss.According to simulations in literature and real-world studies,Image steganography proved to be an effectivemethod for secure communication on VANETs,even in difficult network conditions.In this research,we also explore a variety of steganography approaches for vehicular ad-hoc network transportation systems like vector embedding,statistics,spatial domain(SD),transform domain(TD),distortion,masking,and filtering.This study possibly shall help researchers to improve vehicle networks’ability to communicate securely and lay the door for innovative steganography methods.

Elevating Image Steganography:A Fusion of MSB Matching and LSB Substitution for Enhanced Concealment Capabilities

In today’s rapidly evolving landscape of communication technologies,ensuring the secure delivery of sensitive data has become an essential priority.To overcome these difficulties,different steganography and data encryption methods have been proposed by researchers to secure communications.Most of the proposed steganography techniques achieve higher embedding capacities without compromising visual imperceptibility using LSB substitution.In this work,we have an approach that utilizes a combinationofMost SignificantBit(MSB)matching andLeast Significant Bit(LSB)substitution.The proposed algorithm divides confidential messages into pairs of bits and connects them with the MSBs of individual pixels using pair matching,enabling the storage of 6 bits in one pixel by modifying a maximum of three bits.The proposed technique is evaluated using embedding capacity and Peak Signal-to-Noise Ratio(PSNR)score,we compared our work with the Zakariya scheme the results showed a significant increase in data concealment capacity.The achieved results of ourwork showthat our algorithmdemonstrates an improvement in hiding capacity from11%to 22%for different data samples while maintaining a minimumPeak Signal-to-Noise Ratio(PSNR)of 37 dB.These findings highlight the effectiveness and trustworthiness of the proposed algorithm in securing the communication process and maintaining visual integrity.

Improved Video Steganography with Dual Cover Medium,DNA and Complex Frames

The most valuable resource on the planet is no longer oil,but data.The transmission of this data securely over the internet is another challenge that comes with its ever-increasing value.In order to transmit sensitive information securely,researchers are combining robust cryptography and steganographic approaches.The objective of this research is to introduce a more secure method of video steganography by using Deoxyribonucleic acid(DNA)for embedding encrypted data and an intelligent frame selection algorithm to improve video imperceptibility.In the previous approach,DNA was used only for frame selection.If this DNA is compromised,then our frames with the hidden and unencrypted data will be exposed.Moreover the frame selected in this way were random frames,and no consideration was made to the contents of frames.Hiding data in this way introduces visible artifacts in video.In the proposed approach rather than using DNA for frame selection we have created a fakeDNA out of our data and then embedded it in a video file on intelligently selected frames called the complex frames.Using chaotic maps and linear congruential generators,a unique pixel set is selected each time only from the identified complex frames,and encrypted data is embedded in these random locations.Experimental results demonstrate that the proposed technique shows minimum degradation of the stenographic video hence reducing the very first chances of visual surveillance.Further,the selection of complex frames for embedding and creation of a fake DNA as proposed in this research have higher peak signal-to-noise ratio(PSNR)and reduced mean squared error(MSE)values that indicate improved results.The proposed methodology has been implemented in Matlab.

Topic Controlled Steganography via Graph-to-Text Generation

Generation-based linguistic steganography is a popular research area of information hiding.The text generative steganographic method based on conditional probability coding is the direction that researchers have recently paid attention to.However,in the course of our experiment,we found that the secret information hiding in the text tends to destroy the statistical distribution characteristics of the original text,which indicates that this method has the problem of the obvious reduction of text quality when the embedding rate increases,and that the topic of generated texts is uncontrollable,so there is still room for improvement in concealment.In this paper,we propose a topic-controlled steganography method which is guided by graph-to-text generation.The proposed model can automatically generate steganographic texts carrying secret messages from knowledge graphs,and the topic of the generated texts is controllable.We also provide a graph path coding method with corresponding detailed algorithms for graph-to-text generation.Different from traditional linguistic steganography methods,we encode the secret information during graph path coding rather than using conditional probability.We test our method in different aspects and compare it with other text generative steganographic methods.The experimental results show that the model proposed in this paper can effectively improve the quality of the generated text and significantly improve the concealment of steganographic text.

A New Generative Mathematical Model for Coverless Steganography System Based on Image Generation

The ability of any steganography system to correctly retrieve the secret message is the primary criterion for measuring its efficiency.Recently,researchers have tried to generate a new natural image driven from only the secret message bits rather than using a cover to embed the secret message within it;this is called the stego image.This paper proposes a new secured coverless steganography system using a generative mathematical model based on semi Quick Response(QR)code and maze game image generation.This system consists of two components.The first component contains two processes,encryption process,and hiding process.The encryption process encrypts secret message bits in the form of a semi-QR code image whereas the hiding process conceals the pregenerated semi-QR code in the generated maze game image.On the other hand,the second component contains two processes,extraction and decryption,which are responsible for extracting the semi-QR code from the maze game image and then retrieving the original secret message from the extracted semi-QR code image,respectively.The results were obtained using the bit error rate(BER)metric.These results confirmed that the system achieved high hiding capacity,good performance,and a high level of robustness against attackers compared with other coverless steganography methods.

Cover Enhancement Method for Audio Steganography Based on Universal Adversarial Perturbations with Sample Diversification

Steganography techniques,such as audio steganography,have been widely used in covert communication.However,the deep neural network,especially the convolutional neural network(CNN),has greatly threatened the security of audio steganography.Besides,existing adversarial attacks-based countermeasures cannot provide general perturbation,and the trans-ferability against unknown steganography detection methods is weak.This paper proposes a cover enhancement method for audio steganography based on universal adversarial perturbations with sample diversification to address these issues.Universal adversarial perturbation is constructed by iteratively optimizing adversarial perturbation,which applies adversarial attack tech-niques,such as Deepfool.Moreover,the sample diversification strategy is designed to improve the transferability of adversarial perturbations in black-box attack scenarios,where two types of common audio-processing operations are considered,including noise addition and moving picture experts group audio layer III(MP3)compression.Furthermore,the perturbation ensemble method is applied to further improve the attacks’transferability by integrating perturbations of different detection networks with heterogeneous architec-tures.Consequently,the single universal adversarial perturbation can enhance different cover audios against a CNN-based detection network.Extensive experiments have been conducted,and the results demonstrate that the average missed-detection probabilities of the proposed method are higher than those of the state-of-the-art methods by 7.3%and 16.6%for known and unknown detection networks,respectively.It verifies the efficiency and transferability of the proposed methods for the cover enhancement of audio steganography.

Optimizing Region of Interest Selection for Effective Embedding in Video Steganography Based on Genetic Algorithms

With the widespread use of the internet,there is an increasing need to ensure the security and privacy of transmitted data.This has led to an intensified focus on the study of video steganography,which is a technique that hides data within a video cover to avoid detection.The effectiveness of any steganography method depends on its ability to embed data without altering the original video’s quality while maintaining high efficiency.This paper proposes a new method to video steganography,which involves utilizing a Genetic Algorithm(GA)for identifying the Region of Interest(ROI)in the cover video.The ROI is the area in the video that is the most suitable for data embedding.The secret data is encrypted using the Advanced Encryption Standard(AES),which is a widely accepted encryption standard,before being embedded into the cover video,utilizing up to 10%of the cover video.This process ensures the security and confidentiality of the embedded data.The performance metrics for assessing the proposed method are the Peak Signalto-Noise Ratio(PSNR)and the encoding and decoding time.The results show that the proposed method has a high embedding capacity and efficiency,with a PSNR ranging between 64 and 75 dBs,which indicates that the embedded data is almost indistinguishable from the original video.Additionally,the method can encode and decode data quickly,making it efficient for real-time applications.

An Enhanced Graphical Authentication Scheme Using Multiple-Image Steganography

Most remote systems require user authentication to access resources.Text-based passwords are still widely used as a standard method of user authentication.Although conventional text-based passwords are rather hard to remember,users often write their passwords down in order to compromise security.One of the most complex challenges users may face is posting sensitive data on external data centers that are accessible to others and do not be controlled directly by users.Graphical user authentication methods have recently been proposed to verify the user identity.However,the fundamental limitation of a graphi-cal password is that it must have a colorful and rich image to provide an adequate password space to maintain security,and when the user clicks and inputs a pass-word between two possible grids,the fault tolerance is adjusted to avoid this situation.This paper proposes an enhanced graphical authentication scheme,which comprises benefits over both recognition and recall-based graphical techniques besides image steganography.The combination of graphical authentication and steganography technologies reduces the amount of sensitive data shared between users and service providers and improves the security of user accounts.To evaluate the effectiveness of the proposed scheme,peak signal-to-noise ratio and mean squared error parameters have been used.

Coverless Image Steganography System Based on Maze Game Generation

The trend of digital information transformation has become a topic of interest.Many data are threatening;thus,protecting such data from attackers is considered an essential process.Recently,a new methodology for data concealing has been suggested by researchers called coverless steganography.Coverless steganography can be accomplished either by building an image database to match its image subblocks with the secret message to obtain the stego image or by generating an image.This paper proposes a coverless image steganography system based on pure image generation using secret message bits with a capacity higher than the other traditional systems.The system uses the secret message to generate the stego image in the form of one of the Intelligence Quotient(IQ)games,the maze.Firstly,a full grid is generated with several specific rows and columns determined from the number of bits of the secret message.Then,these bits are fed to the full grid to form the maze game stego image.Finally,the generated maze game stego image is sent to the recipient.The experimental results,using the Bit Error Rate(BER),were conducted,and confirmed the strength of this system represented by a high capacity,perfect performance,robustness,and stronger hiding system compared with existing coverless steganography systems.

Securing Technique Using Pattern-Based LSB Audio Steganography and Intensity-Based Visual Cryptography

With the increasing need of sensitive or secret data transmission through public network,security demands using cryptography and steganography are becoming a thirsty research area of last few years.These two techniques can be merged and provide better security which is nowadays extremely required.The proposed system provides a novel method of information security using the techniques of audio steganography combined with visual cryptography.In this system,we take a secret image and divide it into several subparts to make more than one incomprehensible sub-images using the method of visual cryptography.Each of the sub-images is then hidden within individual cover audio files using audio steganographic techniques.The cover audios are then sent to the required destinations where reverse steganography schemes are applied to them to get the incomprehensible component images back.At last,all the sub-images are superimposed to get the actual secret image.This method is very secure as it uses a two-step security mechanism to maintain secrecy.The possibility of interception is less in this technique because one must have each piece of correct sub-image to regenerate the actual secret image.Without superimposing every one of the sub-images meaningful secret images cannot be formed.Audio files are composed of densely packed bits.The high density of data in audio makes it hard for a listener to detect the manipulation due to the proposed time-domain audio steganographic method.

Analysis and Improvement of Steganography Protocol Based on Bell States in Noise Environment

In the field of quantum communication,quantum steganography is an important branch of quantum information hiding.In a realistic quantum communication system,quantum noises are unavoidable and will seriously impact the safety and reliability of the quantum steganographic system.Therefore,it is very important to analyze the influence of noise on the quantum steganography protocol and how to reduce the effect of noise.This paper takes the quantum steganography protocol proposed in 2010 as an example to analyze the effects of noises on information qubits and secret message qubits in the four primary quantum noise environments.The results show that when the noise factor of one quantum channel noise is known,the size of the noise factor of the other quantum channel can be adjusted accordingly,such as artificially applying noise,so that the influence of noises on the protocol is minimized.In addition,this paper also proposes a method of improving the efficiency of the steganographic protocol in a noisy environment.

Steganography in binary image by checking data-carrying eligibility of boundary pixels

We present a novel scheme for embedding secret data into a binary image without introducing noticeable artifacts. Unlike some block-based methods, the proposed scheme encodes the secret bits directly into boundary pixels by checking each pixel of the cover image in a pseudo-random order for embedding eligibility. A set of rules ensures correct identification of data-carrying pixels in blind extraction. The proposed scheme does not generate isolated dots, and can incorporate various coding methods such as matrix encoding to further improve the embedding performance. It is shown that up to one fourth of the boundary pixels may be used to carry secret data. Experimental results indicate that the method can achieve good visual quality with fairly large data capacity.

Coverless Steganography for Digital Images Based on a Generative Model

In this paper,we propose a novel coverless image steganographic scheme based on a generative model.In our scheme,the secret image is first fed to the generative model database,to generate a meaning-normal and independent image different from the secret image.The generated image is then transmitted to the receiver and fed to the generative model database to generate another image visually the same as the secret image.Thus,we only need to transmit the meaning-normal image which is not related to the secret image,and we can achieve the same effect as the transmission of the secret image.This is the first time to propose the coverless image information steganographic scheme based on generative model,compared with the traditional image steganography.The transmitted image is not embedded with any information of the secret image in this method,therefore,can effectively resist steganalysis tools.Experimental results show that our scheme has high capacity,security and reliability.

GAN-GLS:Generative Lyric Steganography Based on Generative Adversarial Networks

Steganography based on generative adversarial networks(GANs)has become a hot topic among researchers.Due to GANs being unsuitable for text fields with discrete characteristics,researchers have proposed GANbased steganography methods that are less dependent on text.In this paper,we propose a new method of generative lyrics steganography based on GANs,called GAN-GLS.The proposed method uses the GAN model and the largescale lyrics corpus to construct and train a lyrics generator.In this method,the GAN uses a previously generated line of a lyric as the input sentence in order to generate the next line of the lyric.Using a strategy based on the penalty mechanism in training,the GAN model generates non-repetitive and diverse lyrics.The secret information is then processed according to the data characteristics of the generated lyrics in order to hide information.Unlike other text generation-based linguistic steganographic methods,our method changes the way that multiple generated candidate items are selected as the candidate groups in order to encode the conditional probability distribution.The experimental results demonstrate that our method can generate highquality lyrics as stego-texts.Moreover,compared with other similar methods,the proposed method achieves good performance in terms of imperceptibility,embedding rate,effectiveness,extraction success rate and security.

Coverless Image Steganography Based on Image Segmentation

To resist the risk of the stego-image being maliciously altered during transmission,we propose a coverless image steganography method based on image segmentation.Most existing coverless steganography methods are based on whole feature mapping,which has poor robustness when facing geometric attacks,because the contents in the image are easy to lost.To solve this problem,we use ResNet to extract semantic features,and segment the object areas from the image through Mask RCNN for information hiding.These selected object areas have ethical structural integrity and are not located in the visual center of the image,reducing the information loss of malicious attacks.Then,these object areas will be binarized to generate hash sequences for information mapping.In transmission,only a set of stego-images unrelated to the secret information are transmitted,so it can fundamentally resist steganalysis.At the same time,since both Mask RCNN and ResNet have excellent robustness,pre-training the model through supervised learning can achieve good performance.The robust hash algorithm can also resist attacks during transmission.Although image segmentation will reduce the capacity,multiple object areas can be extracted from an image to ensure the capacity to a certain extent.Experimental results show that compared with other coverless image steganography methods,our method is more robust when facing geometric attacks.

Information hiding with adaptive steganography based on novel fuzzy edge identification

The evolution in communication techniques has created wide threats for crucial information transfer through a communication channel. Covert communication with steganography is a skill of concealing secret information within cover object and hence shields the data theft over rapidly growing network.Recently, diverse steganography techniques using edge identification have been proposed in literature.Numerous methods however utilize certain pixels in the cover image for inserting edge information,resulting in significant deformation. The conventional edge detection method limits the deployment of edge detection in steganography as concealing the information would introduce some variations to the cover image. Hence inserting data in pixel areas recognized by existing conventional edge detection techniques like canny cannot ensure the recognition of the exact edge locations for the cover and stego images. In this paper, an Adaptive steganography method based on novel fuzzy edge identification is proposed. The method proposed is proficient of estimating the precise edge areas of a cover image and also ensures the exact edge location after embedding the secret message. Experimental results reveal that the technique has attained good imperceptibility compared to the Hayat AI-Dmour and Ahmed AIAni Edge XOR method in spatial domain.

An Efficient Sound and Data Steganography Based Secure Authentication System

The prodigious advancements in contemporary technologies have also brought in the situation of unprecedented cyber-attacks.Further,the pin-based security system is an inadequate mechanism for handling such a scenario.The reason is that hackers use multiple strategies for evading security systems and thereby gaining access to private data.This research proposes to deploy diverse approaches for authenticating and securing a connection amongst two devices/gadgets via sound,thereby disregarding the pins’manual verification.Further,the results demonstrate that the proposed approaches outperform conventional pin-based authentication or QR authentication approaches.Firstly,a random signal is encrypted,and then it is transformed into a wave file,after which it gets transmitted in a short burst via the device’s speakers.Subsequently,the other device/gadget captures these audio bursts through its microphone and decrypts the audio signal for getting the essential data for pairing.Besides,this model requires two devices/gadgets with speakers and a microphone,and no extra hardware such as a camera,for reading the QR code is required.The first module is tested with realtime data and generates high scores for the widely accepted accuracy metrics,including precision,Recall,F1 score,entropy,and mutual information(MI).Additionally,this work also proposes a module helps in a secured transmission of sensitive data by encrypting it over images and other files.This steganographic module includes two-stage encryption with two different encryption algorithms to transmit data by embedding inside a file.Several encryption algorithms and their combinations are taken for this system to compare the resultant file size.Both these systems engender high accuracies and provide secure connectivity,leading to a sustainable communication ecosystem.

Privacy Protection for Medical Images Based on DenseNet and Coverless Steganography

With the development of the internet of medical things(IoMT),the privacy protection problem has become more and more critical.In this paper,we propose a privacy protection scheme for medical images based on DenseNet and coverless steganography.For a given group of medical images of one patient,DenseNet is used to regroup the images based on feature similarity comparison.Then the mapping indexes can be constructed based on LBP feature and hash generation.After mapping the privacy information with the hash sequences,the corresponding mapped indexes of secret information will be packed together with the medical images group and released to the authorized user.The user can extract the privacy information successfully with a similar method of feature analysis and index construction.The simulation results show good performance of robustness.And the hiding success rate also shows good feasibility and practicability for application.Since the medical images are kept original without embedding and modification,the performance of crack resistance is outstanding and can keep better quality for diagnosis compared with traditional schemes with data embedding.

Steganography Using Reversible Texture Synthesis Based on Seeded Region Growing and LSB

Steganography technology has been widely used in data transmission with secret information.However,the existing steganography has the disadvantages of low hidden information capacity,poor visual effect of cover images,and is hard to guarantee security.To solve these problems,steganography using reversible texture synthesis based on seeded region growing and LSB is proposed.Secret information is embedded in the process of synthesizing texture image from the existing natural texture.Firstly,we refine the visual effect.Abnormality of synthetic texture cannot be fully prevented if no approach of controlling visual effect is applied in the process of generating synthetic texture.We use seeded region growing algorithm to ensure texture’s similar local appearance.Secondly,the size and capacity of image can be decreased by introducing the information segmentation,because the capacity of the secret information is proportional to the size of the synthetic texture.Thirdly,enhanced security is also a contribution in this research,because our method does not need to transmit parameters for secret information extraction.LSB is used to embed these parameters in the synthetic texture.

Defining Embedding Distortion for Intra Prediction Mode-Based Video Steganography

In this paper,an effective intra prediction mode-based video strganography is proposed.Secret messages are embedded during the intra prediction of the video encoding without causing large embedding impact.The influence on the sum of absolute difference(SAD)in intra prediction modes(IPMs)reversion phenomenon is sharp when modifying IPMs.It inspires us to take the SAD prediction deviation(SPD)to define the distortion function.What is more,the mapping rule between IPMs and the codewords is introduced to further reduce the SPD values of each intra block.Syndrome-trellis code(STC)is used as the practical embedding implementation.Experimental results demonstrate that our proposed steganographic scheme presents high undetectability compared with existing IPMs-based steganographic approaches.It also outperforms these schemes on stego video quality.