Traditional steganography conceals information by modifying cover data,but steganalysis tools easily detect such alterations.While deep learning-based steganography often involves high training costs and complex deplo...Traditional steganography conceals information by modifying cover data,but steganalysis tools easily detect such alterations.While deep learning-based steganography often involves high training costs and complex deployment.Diffusion model-based methods face security vulnerabilities,particularly due to potential information leakage during generation.We propose a fixed neural network image steganography framework based on secure diffu-sion models to address these challenges.Unlike conventional approaches,our method minimizes cover modifications through neural network optimization,achieving superior steganographic performance in human visual perception and computer vision analyses.The cover images are generated in an anime style using state-of-the-art diffusion models,ensuring the transmitted images appear more natural.This study introduces fixed neural network technology that allows senders to transmit only minimal critical information alongside stego-images.Recipients can accurately reconstruct secret images using this compact data,significantly reducing transmission overhead compared to conventional deep steganography.Furthermore,our framework innovatively integrates ElGamal,a cryptographic algorithm,to protect critical information during transmission,enhancing overall system security and ensuring end-to-end information protection.This dual optimization of payload reduction and cryptographic reinforcement establishes a new paradigm for secure and efficient image steganography.展开更多
Steganography is a technology that discreetly embeds secret information into the redundant space of a carrier,enabling covert communication.As generative models continue to advance,steganography has evolved from tradi...Steganography is a technology that discreetly embeds secret information into the redundant space of a carrier,enabling covert communication.As generative models continue to advance,steganography has evolved from traditional modification-based methods to generative steganography,which includes generative linguistic and image based forms.However,while large model agents are rapidly emerging,no method has exploited the stable redundant space in their action processes.Inspired by this insightful observation,we propose a steganographic method leveraging large model agents,employing their actions to conceal secret messages.In this paper,we introduce StegoAgent,a generative steganography framework based on graphical user interface(GUI)agents,which effectively demonstrates the remarkable potential and effectiveness of large model agent-based steganographic methods.展开更多
Linguistic steganography(LS)aims to embed secret information into normal natural text for covert communication.It includes modification-based(MLS)and generation-based(GLS)methods.MLS often relies on limited manual rul...Linguistic steganography(LS)aims to embed secret information into normal natural text for covert communication.It includes modification-based(MLS)and generation-based(GLS)methods.MLS often relies on limited manual rules,resulting in low embedding capacity,while GLS achieves higher embedding capacity through automatic text generation but typically ignores extraction efficiency.To address this,we propose a sentence attribute encodingbased MLS method that enhances extraction efficiency while maintaining strong performance.The proposed method designs a lightweight semantic attribute analyzer to encode sentence attributes for embedding secret information.When the attribute values of the cover sentence differ from the secret information to be embedded,a semantic attribute adjuster based on paraphrasing is used to automatically generate paraphrase sentences of the target attribute,thereby improving the problem of insufficient manual rules.During the extraction,secret information can be extracted solely by employing the semantic attribute analyzer,thereby eliminating the dependence on the paraphrasing generation model.Experimental results show that thismethod achieves an extraction speed of 1141.54 bits/sec,compared with the existing methods,it has remarkable advantages regarding extraction speed.Meanwhile,the stego text generated by thismethod respectively reaches 68.53,39.88,and 80.77 on BLEU,△PPL,and BERTScore.Compared with the existing methods,the text quality is effectively improved.展开更多
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 w...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.展开更多
Information steganography has received more and more attention from scholars nowadays,especially in the area of image steganography,which uses image content to transmit information and makes the existence of secret in...Information steganography has received more and more attention from scholars nowadays,especially in the area of image steganography,which uses image content to transmit information and makes the existence of secret information undetectable.To enhance concealment and security,the Steganography without Embedding(SWE)method has proven effective in avoiding image distortion resulting from cover modification.In this paper,a novel encrypted communication scheme for image SWE is proposed.It reconstructs the image into a multi-linked list structure consisting of numerous nodes,where each pixel is transformed into a single node with data and pointer domains.By employing a special addressing algorithm,the optimal linked list corresponding to the secret information can be identified.The receiver can restore the secretmessage fromthe received image using only the list header position information.The scheme is based on the concept of coverless steganography,eliminating the need for any modifications to the cover image.It boasts high concealment and security,along with a complete message restoration rate,making it resistant to steganalysis.Furthermore,this paper proposes linked-list construction schemeswithin theproposedframework,which caneffectively resist a variety of attacks,includingnoise attacks and image compression,demonstrating a certain degree of robustness.To validate the proposed framework,practical tests and comparisons are conducted using multiple datasets.The results affirm the framework’s commendable performance in terms of message reduction rate,hidden writing capacity,and robustness against diverse attacks.展开更多
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 technique...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.展开更多
In Saudi Arabia,drones are increasingly used in different sensitive domains like military,health,and agriculture to name a few.Typically,drone cameras capture aerial images of objects and convert them into crucial dat...In Saudi Arabia,drones are increasingly used in different sensitive domains like military,health,and agriculture to name a few.Typically,drone cameras capture aerial images of objects and convert them into crucial data,alongside collecting data from distributed sensors supplemented by location data.The interception of the data sent from the drone to the station can lead to substantial threats.To address this issue,highly confidential protection methods must be employed.This paper introduces a novel steganography approach called the Shuffling Steganography Approach(SSA).SSA encompasses five fundamental stages and three proposed algorithms,designed to enhance security through strategic encryption and data hiding techniques.Notably,this method introduces advanced resistance to brute force attacks by employing predefined patterns across a wide array of images,complicating unauthorized access.The initial stage involves encryption,dividing,and disassembling the encrypted data.A small portion of the encrypted data is concealed within the text(Algorithm 1)in the third stage.Subsequently,the parts are merged and mixed(Algorithm 2),and finally,the composed text is hidden within an image(Algorithm 3).Through meticulous investigation and comparative analysis with existing methodologies,the proposed approach demonstrates superiority across various pertinent criteria,including robustness,secret message size capacity,resistance to multiple attacks,and multilingual support.展开更多
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...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.展开更多
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 pix...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.展开更多
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 stegan...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.展开更多
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 independ...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.展开更多
In order to optionally regulate embedding capacity and embedding transparency according to user's requirements in voice-over-IP(VoIP) steganography,a dynamic matrix encoding strategy(DMES) was presented.Differing ...In order to optionally regulate embedding capacity and embedding transparency according to user's requirements in voice-over-IP(VoIP) steganography,a dynamic matrix encoding strategy(DMES) was presented.Differing from the traditional matrix encoding strategy,DMES dynamically chose the size of each message group in a given set of adoptable message sizes.The appearance possibilities of all adoptable sizes were set in accordance with the desired embedding performance(embedding rate or bit-change rate).Accordingly,a searching algorithm that could provide an optimal combination of appearance possibilities was proposed.Furthermore,the roulette wheel algorithm was employed to determine the size of each message group according to the optimal combination of appearance possibilities.The effectiveness of DMES was evaluated in StegVoIP,which is a typical covert communication system based on VoIP.The experimental results demonstrate that DMES can adjust embedding capacity and embedding transparency effectively and flexibly,and achieve the desired embedding performance in any case.For the desired embedding rate,the average errors are not more than 0.000 8,and the standard deviations are not more than 0.002 0;for the desired bit-change rate,the average errors are not more than 0.001 4,and the standard deviations are not more than 0.002 6.展开更多
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...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.展开更多
The rapid development of data communication in modern era demands secure exchange of information. Steganography is an established method for hiding secret data from an unauthorized access into a cover object in such a...The rapid development of data communication in modern era demands secure exchange of information. Steganography is an established method for hiding secret data from an unauthorized access into a cover object in such a way that it is invisible to human eyes. The cover object can be image, text, audio,or video. This paper proposes a secure steganography algorithm that hides a bitstream of the secret text into the least significant bits（LSBs） of the approximation coefficients of the integer wavelet transform（IWT） of grayscale images as well as each component of color images to form stego-images. The embedding and extracting phases of the proposed steganography algorithms are performed using the MATLAB software. Invisibility, payload capacity, and security in terms of peak signal to noise ratio（PSNR） and robustness are the key challenges to steganography. The statistical distortion between the cover images and the stego-images is measured by using the mean square error（MSE） and the PSNR, while the degree of closeness between them is evaluated using the normalized cross correlation（NCC）. The experimental results show that, the proposed algorithms can hide the secret text with a large payload capacity with a high level of security and a higher invisibility. Furthermore, the proposed technique is computationally efficient and better results for both PSNR and NCC are achieved compared with the previous algorithms.展开更多
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 ...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.展开更多
Current image steganography methods are working by assigning an image as a cover file then embed the payload within it by modifying its pixels,creating the stego image.However,the left traces that are caused by these ...Current image steganography methods are working by assigning an image as a cover file then embed the payload within it by modifying its pixels,creating the stego image.However,the left traces that are caused by these modifications will make steganalysis algorithms easily detect the hidden payload.A coverless data hiding concept is proposed to solve this issue.Coverless does not mean that cover is not required,or the payload can be transmitted without a cover.Instead,the payload is embedded by cover generation or a secret message mapping between the cover file and the payload.In this paper,a new coverless image steganography method has been proposed based on the jigsaw puzzle image generation driven by a secret message.Firstly,the image is divided into equal rows then further divided into equal columns,creating blocks(i.e.,sub-images).Then,according to secret message bits and a proposed mapping function,each block will have tabs/blanks to get the shape of a puzzle piece creating a fully shaped jigsaw puzzle stego-image.After that,the generated jigsaw puzzle image is sent to the receiver.Experimental results and analysis show a good performance in the hiding capacity,security,and robustness compared with existing coverless image steganography methods.展开更多
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 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.展开更多
Rapid advancements of the Industrial Internet of Things(IIoT)and artificial intelligence(AI)pose serious security issues by revealing secret data.Therefore,security data becomes a crucial issue in IIoT communication w...Rapid advancements of the Industrial Internet of Things(IIoT)and artificial intelligence(AI)pose serious security issues by revealing secret data.Therefore,security data becomes a crucial issue in IIoT communication where secrecy needs to be guaranteed in real time.Practically,AI techniques can be utilized to design image steganographic techniques in IIoT.In addition,encryption techniques act as an important role to save the actual information generated from the IIoT devices to avoid unauthorized access.In order to accomplish secure data transmission in IIoT environment,this study presents novel encryption with image steganography based data hiding technique(EISDHT)for IIoT environment.The proposed EIS-DHT technique involves a new quantum black widow optimization(QBWO)to competently choose the pixel values for hiding secrete data in the cover image.In addition,the multi-level discrete wavelet transform(DWT)based transformation process takes place.Besides,the secret image is divided into three R,G,and B bands which are then individually encrypted using Blowfish,Twofish,and Lorenz Hyperchaotic System.At last,the stego image gets generated by placing the encrypted images into the optimum pixel locations of the cover image.In order to validate the enhanced data hiding performance of the EIS-DHT technique,a set of simulation analyses take place and the results are inspected interms of different measures.The experimental outcomes stated the supremacy of the EIS-DHT technique over the other existing techniques and ensure maximum security.展开更多
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 a...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.展开更多
Steganography aims to hide the messages from unauthorized persons for various purposes,e.g.,military correspondence,financial transaction data.Securing the data during transmission is of utmost importance these days.T...Steganography aims to hide the messages from unauthorized persons for various purposes,e.g.,military correspondence,financial transaction data.Securing the data during transmission is of utmost importance these days.The confidentiality,integrity,and availability of the data are at risk because of the emerging technologies and complexity in software applications,and therefore,there is a need to secure such systems and data.There are various methodologies to deal with security issues when utilizing an open system like the Internet.This research proposes a new technique in steganography within RGB shading space to achieve enhanced security compared with existing systems.We evaluate our approach with the help of diverse image quality evaluation techniques including MSE(Mean Square Error),RMSE(Root Mean Square Error),PSNR(Peak Signal-to-Noise Ratio),MAE(Mean Absolute Error),NCC(Normalized Cross-Correlation)and SSIM(Structural Similarity Index).Our experimental results demonstrate improved strength,intangibility,and security when contrasted with existing techniques and vindicate the effectiveness of this exploration work.The proposed approach achieved a 3.6701%average higher score for PSNR Correlation than the next best existing approach.Moreover,in PSNR with a variable amount of cipher embedded in the same images of the same dimensions,the proposed approach attained a 5.22%better score.Embedding the same size of cipher in images of different size resulted a 3.56%better score.展开更多
基金supported in part by the National Natural Science Foundation of China under Grants 62102450,62272478 and the Independent Research Project of a Certain Unit under Grant ZZKY20243127。
文摘Traditional steganography conceals information by modifying cover data,but steganalysis tools easily detect such alterations.While deep learning-based steganography often involves high training costs and complex deployment.Diffusion model-based methods face security vulnerabilities,particularly due to potential information leakage during generation.We propose a fixed neural network image steganography framework based on secure diffu-sion models to address these challenges.Unlike conventional approaches,our method minimizes cover modifications through neural network optimization,achieving superior steganographic performance in human visual perception and computer vision analyses.The cover images are generated in an anime style using state-of-the-art diffusion models,ensuring the transmitted images appear more natural.This study introduces fixed neural network technology that allows senders to transmit only minimal critical information alongside stego-images.Recipients can accurately reconstruct secret images using this compact data,significantly reducing transmission overhead compared to conventional deep steganography.Furthermore,our framework innovatively integrates ElGamal,a cryptographic algorithm,to protect critical information during transmission,enhancing overall system security and ensuring end-to-end information protection.This dual optimization of payload reduction and cryptographic reinforcement establishes a new paradigm for secure and efficient image steganography.
基金supported in part by the National Natural Science Foundation of China under Grant Nos.62472398 and U2336206.
文摘Steganography is a technology that discreetly embeds secret information into the redundant space of a carrier,enabling covert communication.As generative models continue to advance,steganography has evolved from traditional modification-based methods to generative steganography,which includes generative linguistic and image based forms.However,while large model agents are rapidly emerging,no method has exploited the stable redundant space in their action processes.Inspired by this insightful observation,we propose a steganographic method leveraging large model agents,employing their actions to conceal secret messages.In this paper,we introduce StegoAgent,a generative steganography framework based on graphical user interface(GUI)agents,which effectively demonstrates the remarkable potential and effectiveness of large model agent-based steganographic methods.
基金supported by the National Natural Science Foundation of China under Grant 61972057Hunan Provincial Natural Science Foundation of China under Grant 2022JJ30623.
文摘Linguistic steganography(LS)aims to embed secret information into normal natural text for covert communication.It includes modification-based(MLS)and generation-based(GLS)methods.MLS often relies on limited manual rules,resulting in low embedding capacity,while GLS achieves higher embedding capacity through automatic text generation but typically ignores extraction efficiency.To address this,we propose a sentence attribute encodingbased MLS method that enhances extraction efficiency while maintaining strong performance.The proposed method designs a lightweight semantic attribute analyzer to encode sentence attributes for embedding secret information.When the attribute values of the cover sentence differ from the secret information to be embedded,a semantic attribute adjuster based on paraphrasing is used to automatically generate paraphrase sentences of the target attribute,thereby improving the problem of insufficient manual rules.During the extraction,secret information can be extracted solely by employing the semantic attribute analyzer,thereby eliminating the dependence on the paraphrasing generation model.Experimental results show that thismethod achieves an extraction speed of 1141.54 bits/sec,compared with the existing methods,it has remarkable advantages regarding extraction speed.Meanwhile,the stego text generated by thismethod respectively reaches 68.53,39.88,and 80.77 on BLEU,△PPL,and BERTScore.Compared with the existing methods,the text quality is effectively improved.
基金Dr.Arshiya Sajid Ansari would like to thank the Deanship of Scientific Research at Majmaah University for supporting this work under Project No.R-2023-910.
文摘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.
基金supported in part by the National Natural Science Foundation of China(Nos.62372083,62072074,62076054,62027827,62002047)the Sichuan Science and Technology Innovation Platform and Talent Plan(No.2022JDJQ0039)+2 种基金the Sichuan Science and Technology Support Plan(Nos.2024NSFTD0005,2022YFQ0045,2022YFS0220,2023YFS0020,2023YFS0197,2023YFG0148)the CCF-Baidu Open Fund(No.202312)the Medico-Engineering Cooperation Funds from University of Electronic Science and Technology of China(Nos.ZYGX2021YGLH212,ZYGX2022YGRH012).
文摘Information steganography has received more and more attention from scholars nowadays,especially in the area of image steganography,which uses image content to transmit information and makes the existence of secret information undetectable.To enhance concealment and security,the Steganography without Embedding(SWE)method has proven effective in avoiding image distortion resulting from cover modification.In this paper,a novel encrypted communication scheme for image SWE is proposed.It reconstructs the image into a multi-linked list structure consisting of numerous nodes,where each pixel is transformed into a single node with data and pointer domains.By employing a special addressing algorithm,the optimal linked list corresponding to the secret information can be identified.The receiver can restore the secretmessage fromthe received image using only the list header position information.The scheme is based on the concept of coverless steganography,eliminating the need for any modifications to the cover image.It boasts high concealment and security,along with a complete message restoration rate,making it resistant to steganalysis.Furthermore,this paper proposes linked-list construction schemeswithin theproposedframework,which caneffectively resist a variety of attacks,includingnoise attacks and image compression,demonstrating a certain degree of robustness.To validate the proposed framework,practical tests and comparisons are conducted using multiple datasets.The results affirm the framework’s commendable performance in terms of message reduction rate,hidden writing capacity,and robustness against diverse attacks.
基金Taif University Researchers Supporting Project No.(TURSP-2020/77),Taif university,Taif,Saudi Arabia.
文摘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.
基金funded by the Research Deanship of the Islamic University of Madinah under grant number 966.
文摘In Saudi Arabia,drones are increasingly used in different sensitive domains like military,health,and agriculture to name a few.Typically,drone cameras capture aerial images of objects and convert them into crucial data,alongside collecting data from distributed sensors supplemented by location data.The interception of the data sent from the drone to the station can lead to substantial threats.To address this issue,highly confidential protection methods must be employed.This paper introduces a novel steganography approach called the Shuffling Steganography Approach(SSA).SSA encompasses five fundamental stages and three proposed algorithms,designed to enhance security through strategic encryption and data hiding techniques.Notably,this method introduces advanced resistance to brute force attacks by employing predefined patterns across a wide array of images,complicating unauthorized access.The initial stage involves encryption,dividing,and disassembling the encrypted data.A small portion of the encrypted data is concealed within the text(Algorithm 1)in the third stage.Subsequently,the parts are merged and mixed(Algorithm 2),and finally,the composed text is hidden within an image(Algorithm 3).Through meticulous investigation and comparative analysis with existing methodologies,the proposed approach demonstrates superiority across various pertinent criteria,including robustness,secret message size capacity,resistance to multiple attacks,and multilingual support.
基金This work was supported by the National Natural Science Foundation of China(Nos.61373131,61303039,61232016,61501247)the Six Talent Peaks Project of Jiangsu Province(Grant No.2015-XXRJ-013)+3 种基金Natural Science Foundation of Jiangsu Province(Grant No.BK20171458)the Natural Science Foundation of the Higher Education Institutions of Jiangsu Province(China under Grant No.16KJB520030)Sichuan Youth Science and Technique Foundation(No.2017JQ0048)NUIST Research Foundation for Talented Scholars(2015r014),PAPD and CICAEET funds.
文摘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.
基金Project supported by the National Natural Science Foundation of China （Grant Nos.60372090, 60502039）, and the Key Project of Shanghai Municipality for Basic Research （Grant No.04JC14037）
文摘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.
基金This work was supported in part by the National Natural Science Foundation of China under Grant 61872134,61672222,author Y.L.Liu,http://www.nsfc.gov.cn/in part by Science and Technology Development Center of the Ministry of Education under Grant 2019J01020,author Y.L.Liu,http://www.moe.gov.cn/+1 种基金in part by Science and Technology Project of Transport Department of Hunan Province under Grant 201935,author Y.L.Liu,http://jtt.hunan.gov.cn/Science and Technology Program of Changsha City under Grant kh200519,kq2004021,author Y.L.Liu,http://kjj.changsha.gov.cn/.
文摘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.
基金This paper was supported by the National Natural Science Foundation of China(No.U1204606)the Key Programs for Science and Technology Development of Henan Province(No.172102210335)Key Scientific Research Projects in Henan Universities(No.16A520058).
文摘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.
基金Project(2009AA01A402) supported by the National High-Tech Research and Development Program of ChinaProject(NCET-06-0650) supported by Program for New Century Excellent Talents in University Project(IRT-0725) supported by Program for Changjiang Scholars and Innovative Research Team in Chinese University
文摘In order to optionally regulate embedding capacity and embedding transparency according to user's requirements in voice-over-IP(VoIP) steganography,a dynamic matrix encoding strategy(DMES) was presented.Differing from the traditional matrix encoding strategy,DMES dynamically chose the size of each message group in a given set of adoptable message sizes.The appearance possibilities of all adoptable sizes were set in accordance with the desired embedding performance(embedding rate or bit-change rate).Accordingly,a searching algorithm that could provide an optimal combination of appearance possibilities was proposed.Furthermore,the roulette wheel algorithm was employed to determine the size of each message group according to the optimal combination of appearance possibilities.The effectiveness of DMES was evaluated in StegVoIP,which is a typical covert communication system based on VoIP.The experimental results demonstrate that DMES can adjust embedding capacity and embedding transparency effectively and flexibly,and achieve the desired embedding performance in any case.For the desired embedding rate,the average errors are not more than 0.000 8,and the standard deviations are not more than 0.002 0;for the desired bit-change rate,the average errors are not more than 0.001 4,and the standard deviations are not more than 0.002 6.
基金This work was supported in part by the National Natural Science Foundation of China under Grant 61772561,author J.Q,http://www.nsfc.gov.cn/in part by the Key Research and Development Plan of Hunan Province under Grant 2018NK2012,author J.Q,http://kjt.hunan.gov.cn/+3 种基金in part by the Science Research Projects of Hunan Provincial Education Department under Grant 18A174,author X.X,http://kxjsc.gov.hnedu.cn/in part by the Degree&Postgraduate Education Reform Project of Hunan Province under Grant 2019JGYB154,author J.Q,http://xwb.gov.hnedu.cn/in part by the Postgraduate Excellent teaching team Project of Hunan Province under Grant[2019]370-133,author J.Q,http://xwb.gov.hnedu.cn/and in part by the Postgraduate Education and Teaching Reform Project of Central South University of Forestry&Technology under Grant 2019JG013,author X.X,http://jwc.csuft.edu.cn/.
文摘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.
文摘The rapid development of data communication in modern era demands secure exchange of information. Steganography is an established method for hiding secret data from an unauthorized access into a cover object in such a way that it is invisible to human eyes. The cover object can be image, text, audio,or video. This paper proposes a secure steganography algorithm that hides a bitstream of the secret text into the least significant bits（LSBs） of the approximation coefficients of the integer wavelet transform（IWT） of grayscale images as well as each component of color images to form stego-images. The embedding and extracting phases of the proposed steganography algorithms are performed using the MATLAB software. Invisibility, payload capacity, and security in terms of peak signal to noise ratio（PSNR） and robustness are the key challenges to steganography. The statistical distortion between the cover images and the stego-images is measured by using the mean square error（MSE） and the PSNR, while the degree of closeness between them is evaluated using the normalized cross correlation（NCC）. The experimental results show that, the proposed algorithms can hide the secret text with a large payload capacity with a high level of security and a higher invisibility. Furthermore, the proposed technique is computationally efficient and better results for both PSNR and NCC are achieved compared with the previous algorithms.
文摘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.
基金funded by“Taif University Researchers Supporting Project No.(TURSP-2020/160),Taif University,Taif,Saudi Arabia.”。
文摘Current image steganography methods are working by assigning an image as a cover file then embed the payload within it by modifying its pixels,creating the stego image.However,the left traces that are caused by these modifications will make steganalysis algorithms easily detect the hidden payload.A coverless data hiding concept is proposed to solve this issue.Coverless does not mean that cover is not required,or the payload can be transmitted without a cover.Instead,the payload is embedded by cover generation or a secret message mapping between the cover file and the payload.In this paper,a new coverless image steganography method has been proposed based on the jigsaw puzzle image generation driven by a secret message.Firstly,the image is divided into equal rows then further divided into equal columns,creating blocks(i.e.,sub-images).Then,according to secret message bits and a proposed mapping function,each block will have tabs/blanks to get the shape of a puzzle piece creating a fully shaped jigsaw puzzle stego-image.After that,the generated jigsaw puzzle image is sent to the receiver.Experimental results and analysis show a good performance in the hiding capacity,security,and robustness compared with existing coverless image steganography methods.
文摘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.
基金This research work was funded by Institution Fund projects under Grant No.(IFPRC-215-249-2020)Therefore,authors gratefully acknowledge technical and financial support from the Ministry of Education and King Abdulaziz University,DSR,Jeddah,Saudi Arabia.
文摘Rapid advancements of the Industrial Internet of Things(IIoT)and artificial intelligence(AI)pose serious security issues by revealing secret data.Therefore,security data becomes a crucial issue in IIoT communication where secrecy needs to be guaranteed in real time.Practically,AI techniques can be utilized to design image steganographic techniques in IIoT.In addition,encryption techniques act as an important role to save the actual information generated from the IIoT devices to avoid unauthorized access.In order to accomplish secure data transmission in IIoT environment,this study presents novel encryption with image steganography based data hiding technique(EISDHT)for IIoT environment.The proposed EIS-DHT technique involves a new quantum black widow optimization(QBWO)to competently choose the pixel values for hiding secrete data in the cover image.In addition,the multi-level discrete wavelet transform(DWT)based transformation process takes place.Besides,the secret image is divided into three R,G,and B bands which are then individually encrypted using Blowfish,Twofish,and Lorenz Hyperchaotic System.At last,the stego image gets generated by placing the encrypted images into the optimum pixel locations of the cover image.In order to validate the enhanced data hiding performance of the EIS-DHT technique,a set of simulation analyses take place and the results are inspected interms of different measures.The experimental outcomes stated the supremacy of the EIS-DHT technique over the other existing techniques and ensure maximum security.
基金This work was supported in part by the National Natural Science Foundation of China under Grant 61772561,author J.Q,http://www.nsfc.gov.cn/in part by the Key Research and Development Plan of Hunan Province under Grant 2018NK2012,author J.Q,and 2019SK2022,author H.T,http://kjt.hunan.gov.cn/+4 种基金in part by the Science Research Projects of Hunan Provincial Education Department under Grant 18A174,author X.X,and Grant 19B584,author Y.T,http://kxjsc.gov.hnedu.cn/in part by the Degree&Postgraduate Education Reform Project of Hunan Province under Grant 2019JGYB154,author J.Q,http://xwb.gov.hnedu.cn/in part by the National Natural Science Foundation of Hunan under Grant 2019JJ50866,author L.T,2020JJ4140,author Y.T,and 2020JJ4141,author X.X,http://kjt.hunan.gov.cn/in part by the Postgraduate Excellent teaching team Project of Hunan Province under Grant[2019]370-133,author J.Q,http://xwb.gov.hnedu.cn/and in part by the Postgraduate Education and Teaching Reform Project of Central South University of Forestry&Technology under Grant 2019JG013,author X.X,http://jwc.csuft.edu.cn/.
文摘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.
基金This research is supported by the Higher Education Commission(HEC),Pakistan through its initiative of National Center for Cyber Security for the affiliated Security Testing-Innovative Secured Systems Lab(ISSL)established at University of Engineering&Technology(UET)Peshawar,Grant No.2(1078)/HEC/M&E/2018/707.
文摘Steganography aims to hide the messages from unauthorized persons for various purposes,e.g.,military correspondence,financial transaction data.Securing the data during transmission is of utmost importance these days.The confidentiality,integrity,and availability of the data are at risk because of the emerging technologies and complexity in software applications,and therefore,there is a need to secure such systems and data.There are various methodologies to deal with security issues when utilizing an open system like the Internet.This research proposes a new technique in steganography within RGB shading space to achieve enhanced security compared with existing systems.We evaluate our approach with the help of diverse image quality evaluation techniques including MSE(Mean Square Error),RMSE(Root Mean Square Error),PSNR(Peak Signal-to-Noise Ratio),MAE(Mean Absolute Error),NCC(Normalized Cross-Correlation)and SSIM(Structural Similarity Index).Our experimental results demonstrate improved strength,intangibility,and security when contrasted with existing techniques and vindicate the effectiveness of this exploration work.The proposed approach achieved a 3.6701%average higher score for PSNR Correlation than the next best existing approach.Moreover,in PSNR with a variable amount of cipher embedded in the same images of the same dimensions,the proposed approach attained a 5.22%better score.Embedding the same size of cipher in images of different size resulted a 3.56%better score.
