The situation of intercepted alien pests from imported hides in Hebei during 2013-2014 was systematically analyzed. The results showed that 163 batches of alien pests were intercepted, including 2 batches of quarantin...The situation of intercepted alien pests from imported hides in Hebei during 2013-2014 was systematically analyzed. The results showed that 163 batches of alien pests were intercepted, including 2 batches of quarantine weeds and they both were Italian cocklebur. According to the statistics of original countries, the intercepted hides from 21 countries all had alien pests, in which Australia was the largest number of batches and species of alien pests. The analysis results showed that there was severe risk in the imported hides carrying alien pests, thus to effectively prevent the invasion of alien pests to our country, several quarantine measures should be taken in the future, such as enhancing the quarantine inspection in ports, and promoting the personnel ability of interception and species identification of alien pests.展开更多
A category of chromium (Cr)-containing fertilizers is represented by the fertilizers deriving from byproducts of tanning process. Their use is widespread because of their good agronomic response due to the high conten...A category of chromium (Cr)-containing fertilizers is represented by the fertilizers deriving from byproducts of tanning process. Their use is widespread because of their good agronomic response due to the high content of slow release or- ganic nitrogen (N) and carbon (C). They do not represent an environmental hazard because only the non-toxic form of Cr(III) is present. Productive processes may involve chemical, enzymatic or thermal hydrolysis. The final product is characterized by different contents of peptides and free amino acids depending on the type of hydrolysis. Legislation concerning Cr-containing fertilizers is controversial because often do not consider any scientific evidences;nevertheless, the European Union, the United States and countries as Italy, do not set the restriction to Cr(III) and generally only the presence of the toxic form, Cr(VI), is limited. Depending on its two main oxidation forms, Cr issue has been studied for many years. Several authors confirmed that Cr(VI) is carcinogenic, while Cr(III) is an essential trace element in human and animal diet. In soil Cr(III) has low mobility, whereas Cr(VI) is highly water soluble. However Cr(VI) in soil is quickly reduced to Cr(III);on the contrary oxidation of Cr(III) to Cr(VI) is rarely possible because particular conditions must occur. Only a very small fraction of Cr in soil is available to plant uptake and its translocation in edible parts is limited because it is immobilized in roots as Cr(III). Therefore risks of environmental pollution using these fertilizers are negligible;on the contrary they have positive environmental and agronomical effects. The aim of this review is to deal with the category of the organic fertilizers containing Cr derived from tannery processes focusing on its chemical, productive, legislative, environmental and agronomical aspects. Special attention is given to the ambiguous issue of Cr briefly summarizing the most important studies of the last forty years.展开更多
Data hiding methods involve embedding secret messages into cover objects to enable covert communication in a way that is difficult to detect.In data hiding methods based on image interpolation,the image size is reduce...Data hiding methods involve embedding secret messages into cover objects to enable covert communication in a way that is difficult to detect.In data hiding methods based on image interpolation,the image size is reduced and then enlarged through interpolation,followed by the embedding of secret data into the newly generated pixels.A general improving approach for embedding secret messages is proposed.The approach may be regarded a general model for enhancing the data embedding capacity of various existing image interpolation-based data hiding methods.This enhancement is achieved by expanding the range of pixel values available for embedding secret messages,removing the limitations of many existing methods,where the range is restricted to powers of two to facilitate the direct embedding of bit-based messages.This improvement is accomplished through the application of multiple-based number conversion to the secret message data.The method converts the message bits into a multiple-based number and uses an algorithm to embed each digit of this number into an individual pixel,thereby enhancing the message embedding efficiency,as proved by a theorem derived in this study.The proposed improvement method has been tested through experiments on three well-known image interpolation-based data hiding methods.The results show that the proposed method can enhance the three data embedding rates by approximately 14%,13%,and 10%,respectively,create stego-images with good quality,and resist RS steganalysis attacks.These experimental results indicate that the use of the multiple-based number conversion technique to improve the three interpolation-based methods for embedding secret messages increases the number of message bits embedded in the images.For many image interpolation-based data hiding methods,which use power-of-two pixel-value ranges for message embedding,other than the three tested ones,the proposed improvement method is also expected to be effective for enhancing their data embedding capabilities.展开更多
Generative image steganography is a technique that directly generates stego images from secret infor-mation.Unlike traditional methods,it theoretically resists steganalysis because there is no cover image.Currently,th...Generative image steganography is a technique that directly generates stego images from secret infor-mation.Unlike traditional methods,it theoretically resists steganalysis because there is no cover image.Currently,the existing generative image steganography methods generally have good steganography performance,but there is still potential room for enhancing both the quality of stego images and the accuracy of secret information extraction.Therefore,this paper proposes a generative image steganography algorithm based on attribute feature transformation and invertible mapping rule.Firstly,the reference image is disentangled by a content and an attribute encoder to obtain content features and attribute features,respectively.Then,a mean mapping rule is introduced to map the binary secret information into a noise vector,conforming to the distribution of attribute features.This noise vector is input into the generator to produce the attribute transformed stego image with the content feature of the reference image.Additionally,we design an adversarial loss,a reconstruction loss,and an image diversity loss to train the proposed model.Experimental results demonstrate that the stego images generated by the proposed method are of high quality,with an average extraction accuracy of 99.4%for the hidden information.Furthermore,since the stego image has a uniform distribution similar to the attribute-transformed image without secret information,it effectively resists both subjective and objective steganalysis.展开更多
One sunny day,a little dog with the name Max met a little cat named Lily in the backyard.Max:Hi,Lily!I'm looking for something interesting to do.Do you want to play with me?Lily:Sure,Max!But how 1 can we play?Max:...One sunny day,a little dog with the name Max met a little cat named Lily in the backyard.Max:Hi,Lily!I'm looking for something interesting to do.Do you want to play with me?Lily:Sure,Max!But how 1 can we play?Max:How about hide-and-seek?Lily:Sound②great!You count first,and I'll go hide.展开更多
Establish an efficacy evaluation method for foundation products in vivo and vitro.The hiding power,whiteness,waterproof and anti-sweat effect were evaluated in vitro test,where CR ratio,Individual Type Angle (ITA°...Establish an efficacy evaluation method for foundation products in vivo and vitro.The hiding power,whiteness,waterproof and anti-sweat effect were evaluated in vitro test,where CR ratio,Individual Type Angle (ITA°) and chromatic aberration (E) were measured as evaluation indicators by standard black/white cardboard,artificial leather and artificial sweat.In clinical assessment,the anti-stain,waterproof,anti-sweat effect of the foundation products were evaluated through the ΔE change,before and after the treatment of products by staining,wetting,sweating in forearm skin.There were significant differences in CR ratio of different types of samples on standard black and white cardboards (P<0.05),ITA° of artificial leather has a significant increase after treatment (P<0.05),?E﹤1.5 in black cloth after dipping test,while ΔE﹤1.5 in leather after water and artificial sweat treatment.Clinical assessment showed that ?E ﹤50%,which had no significant difference in human skin color,before and after the test (P>0.05).The change trend of efficacy evaluation in vitro test was basically consistent with that of visual evaluation and clinical assessment,indicated that the efficacy evaluation methods of foundation products in vivo and vitro are intuitive,quantifiable,and can be used to evaluate the efficacy of foundation products.展开更多
Ciphertext-Policy Attribute-Based Encryption(CP-ABE)enables fine-grained access control on ciphertexts,making it a promising approach for managing data stored in the cloud-enabled Internet of Things.But existing schem...Ciphertext-Policy Attribute-Based Encryption(CP-ABE)enables fine-grained access control on ciphertexts,making it a promising approach for managing data stored in the cloud-enabled Internet of Things.But existing schemes often suffer from privacy breaches due to explicit attachment of access policies or partial hiding of critical attribute content.Additionally,resource-constrained IoT devices,especially those adopting wireless communication,frequently encounter affordability issues regarding decryption costs.In this paper,we propose an efficient and fine-grained access control scheme with fully hidden policies(named FHAC).FHAC conceals all attributes in the policy and utilizes bloom filters to efficiently locate them.A test phase before decryption is applied to assist authorized users in finding matches between their attributes and the access policy.Dictionary attacks are thwarted by providing unauthorized users with invalid values.The heavy computational overhead of both the test phase and most of the decryption phase is outsourced to two cloud servers.Additionally,users can verify the correctness of multiple outsourced decryption results simultaneously.Security analysis and performance comparisons demonstrate FHAC's effectiveness in protecting policy privacy and achieving efficient decryption.展开更多
With the rapid expansion of multimedia data,protecting digital information has become increasingly critical.Reversible data hiding offers an effective solution by allowing sensitive information to be embedded in multi...With the rapid expansion of multimedia data,protecting digital information has become increasingly critical.Reversible data hiding offers an effective solution by allowing sensitive information to be embedded in multimedia files while enabling full recovery of the original data after extraction.Audio,as a vital medium in communication,entertainment,and information sharing,demands the same level of security as images.However,embedding data in encrypted audio poses unique challenges due to the trade-offs between security,data integrity,and embedding capacity.This paper presents a novel interpolation-based reversible data hiding algorithm for encrypted audio that achieves scalable embedding capacity.By increasing sample density through interpolation,embedding opportunities are significantly enhanced while maintaining encryption throughout the process.The method further integrates multiple most significant bit(multi-MSB)prediction and Huffman coding to optimize compression and embedding efficiency.Experimental results on standard audio datasets demonstrate the proposed algorithm’s ability to embed up to 12.47 bits per sample with over 9.26 bits per sample available for pure embedding capacity,while preserving full reversibility.These results confirm the method’s suitability for secure applications that demand high embedding capacity and perfect reconstruction of original audio.This work advances reversible data hiding in encrypted audio by offering a secure,efficient,and fully reversible data hiding framework.展开更多
This study introduces an Edge-Based Data Hiding and Extraction Algorithm(EBDHEA)to address the problem of data embedding in images while preserving robust security and high image quality.The algorithm produces three c...This study introduces an Edge-Based Data Hiding and Extraction Algorithm(EBDHEA)to address the problem of data embedding in images while preserving robust security and high image quality.The algorithm produces three classes of pixels from the pixels in the cover image:edges found by the Canny edge detection method,pixels arising from the expansion of neighboring edge pixels,and pixels that are neither edges nor components of the neighboring edge pixels.The number of Least Significant Bits(LSBs)that are used to hide data depends on these classifications.Furthermore,the lossless compression method,Huffman coding,improves image data capacity.To increase the security of the steganographic process,secret messages are encrypted using the XOR encryption technique before being embedded.Metrics such as the Mean Squared Error(MSE),Peak Signal-to-Noise Ratio(PSNR),and Structural Similarity Index Measure(SSIM)are used to assess the efficacy of this algorithm and are compared to previous methods.The findings demonstrate that the suggested approach achieves high similarity between the original and modified images with a maximum PSNR of 60.7 dB for a payload of 18,750 bytes,a maximum SSIM of 0.999 for a payload of 314,572.8 bytes,and a maximum Video Information Fidelity(VIF)of 0.95 for a payload of 23,592 bytes.Normalized Cross-Correlation(NCC)values are very close to 1.In addition,the performance of EBDHEA is implemented on Secure Medical Image Transmission as a real-world example,and the performance is tested against three types of attacks:RS Steganalysis,Chi-square attack,and visual attack,and compared with two deep learning models,such as SRNet and XuNet.展开更多
We explored the effects of algorithmic opacity on employees’playing dumb and evasive hiding rather than rationalized hiding.We examined the mediating role of job insecurity and the moderating role of employee-AI coll...We explored the effects of algorithmic opacity on employees’playing dumb and evasive hiding rather than rationalized hiding.We examined the mediating role of job insecurity and the moderating role of employee-AI collaboration.Participants were 421 full-time employees(female=46.32%,junior employees=31.83%)from a variety of organizations and industries that interact with AI.Employees filled out data on algorithm opacity,job insecurity,knowledge hiding,employee-AI collaboration,and control variables.The results of the structural equation modeling indicated that algorithm opacity exacerbated employees’job insecurity,and job insecurity mediated between algorithm opacity and playing dumb and evasive hiding rather than rationalized hiding.The relationship between algorithmic opacity and playing dumb and evasive hiding was more positive when the level of employee-AI collaboration was higher.These findings suggest that employee-AI collaboration reinforces the indirect relationship between algorithmic opacity and playing dumb and evasive hiding.Our study contributes to research on human and AI collaboration by exploring the dark side of employee-AI collaboration.展开更多
Federated Learning(FL)has emerged as a promising distributed machine learning paradigm that enables multi-party collaborative training while eliminating the need for raw data sharing.However,its reliance on a server i...Federated Learning(FL)has emerged as a promising distributed machine learning paradigm that enables multi-party collaborative training while eliminating the need for raw data sharing.However,its reliance on a server introduces critical security vulnerabilities:malicious servers can infer private information from received local model updates or deliberately manipulate aggregation results.Consequently,achieving verifiable aggregation without compromising client privacy remains a critical challenge.To address these problem,we propose a reversible data hiding in encrypted domains(RDHED)scheme,which designs joint secret message embedding and extraction mechanism.This approach enables clients to embed secret messages into ciphertext redundancy spaces generated during model encryption.During the server aggregation process,the embedded messages from all clients fuse within the ciphertext space to form a joint embedding message.Subsequently,clients can decrypt the aggregated results and extract this joint embedding message for verification purposes.Building upon this foundation,we integrate the proposed RDHED scheme with linear homomorphic hash and digital signatures to design a verifiable privacy-preserving aggregation protocol for single-server architectures(VPAFL).Theoretical proofs and experimental analyses show that VPAFL can effectively protect user privacy,achieve lightweight computational and communication overhead of users for verification,and present significant advantages with increasing model dimension.展开更多
Medical image segmentation,i.e.,labeling structures of interest in medical images,is crucial for disease diagnosis and treatment in radiology.In reversible data hiding in medical images(RDHMI),segmentation consists of...Medical image segmentation,i.e.,labeling structures of interest in medical images,is crucial for disease diagnosis and treatment in radiology.In reversible data hiding in medical images(RDHMI),segmentation consists of only two regions:the focal and nonfocal regions.The focal region mainly contains information for diagnosis,while the nonfocal region serves as the monochrome background.The current traditional segmentation methods utilized in RDHMI are inaccurate for complex medical images,and manual segmentation is time-consuming,poorly reproducible,and operator-dependent.Implementing state-of-the-art deep learning(DL)models will facilitate key benefits,but the lack of domain-specific labels for existing medical datasets makes it impossible.To address this problem,this study provides labels of existing medical datasets based on a hybrid segmentation approach to facilitate the implementation of DL segmentation models in this domain.First,an initial segmentation based on a 33 kernel is performed to analyze×identified contour pixels before classifying pixels into focal and nonfocal regions.Then,several human expert raters evaluate and classify the generated labels into accurate and inaccurate labels.The inaccurate labels undergo manual segmentation by medical practitioners and are scored based on a hierarchical voting scheme before being assigned to the proposed dataset.To ensure reliability and integrity in the proposed dataset,we evaluate the accurate automated labels with manually segmented labels by medical practitioners using five assessment metrics:dice coefficient,Jaccard index,precision,recall,and accuracy.The experimental results show labels in the proposed dataset are consistent with the subjective judgment of human experts,with an average accuracy score of 94%and dice coefficient scores between 90%-99%.The study further proposes a ResNet-UNet with concatenated spatial and channel squeeze and excitation(scSE)architecture for semantic segmentation to validate and illustrate the usefulness of the proposed dataset.The results demonstrate the superior performance of the proposed architecture in accurately separating the focal and nonfocal regions compared to state-of-the-art architectures.Dataset information is released under the following URL:https://www.kaggle.com/lordamoah/datasets(accessed on 31 March 2025).展开更多
This paper proposes an artificial intelligence-based robust information hiding algorithm to address the issue of confidential information being susceptible to noise attacks during transmission.The algorithm we designe...This paper proposes an artificial intelligence-based robust information hiding algorithm to address the issue of confidential information being susceptible to noise attacks during transmission.The algorithm we designed aims to mitigate the impact of various noise attacks on the integrity of secret information during transmission.The method we propose involves encoding secret images into stylized encrypted images and applies adversarial transfer to both the style and content features of the original and embedded data.This process effectively enhances the concealment and imperceptibility of confidential information,thereby improving the security of such information during transmission and reducing security risks.Furthermore,we have designed a specialized attack layer to simulate real-world attacks and common noise scenarios encountered in practical environments.Through adversarial training,the algorithm is strengthened to enhance its resilience against attacks and overall robustness,ensuring better protection against potential threats.Experimental results demonstrate that our proposed algorithm successfully enhances the concealment and unknowability of secret information while maintaining embedding capacity.Additionally,it ensures the quality and fidelity of the stego image.The method we propose not only improves the security and robustness of information hiding technology but also holds practical application value in protecting sensitive data and ensuring the invisibility of confidential information.展开更多
The rapid development of the internet and digital media has provided convenience while also posing a potential risk of steganography abuse.Identifying steganographer is essential in tracing secret information origins ...The rapid development of the internet and digital media has provided convenience while also posing a potential risk of steganography abuse.Identifying steganographer is essential in tracing secret information origins and preventing illicit covert communication online.Accurately discerning a steganographer from many normal users is challenging due to various factors,such as the complexity in obtaining the steganography algorithm,extracting highly separability features,and modeling the cover data.After extensive exploration,several methods have been proposed for steganographer identification.This paper presents a survey of existing studies.Firstly,we provide a concise introduction to the research background and outline the issue of steganographer identification.Secondly,we present fundamental concepts and techniques that establish a general framework for identifying steganographers.Within this framework,state-of-the-art methods are summarized from five key aspects:data acquisition,feature extraction,feature optimization,identification paradigm,and performance evaluation.Furthermore,theoretical and experimental analyses examine the advantages and limitations of these existing methods.Finally,the survey highlights outstanding issues in image steganographer identification that deserve further research.展开更多
Hidden capacity,concealment,security,and robustness are essential indicators of hiding algorithms.Currently,hiding algorithms tend to focus on algorithmic capacity,concealment,and security but often overlook the robus...Hidden capacity,concealment,security,and robustness are essential indicators of hiding algorithms.Currently,hiding algorithms tend to focus on algorithmic capacity,concealment,and security but often overlook the robustness of the algorithms.In practical applications,the container can suffer from damage caused by noise,cropping,and other attacks during transmission,resulting in challenging or even impossible complete recovery of the secret image.An image hiding algorithm based on dynamic region attention in the multi-scale wavelet domain is proposed to address this issue and enhance the robustness of hiding algorithms.In this proposed algorithm,a secret image of size 256×256 is first decomposed using an eight-level Haar wavelet transform.The wavelet transform generates one coefficient in the approximation component and twenty-four detail bands,which are then embedded into the carrier image via a hiding network.During the recovery process,the container image is divided into four non-overlapping parts,each employed to reconstruct a low-resolution secret image.These lowresolution secret images are combined using densemodules to obtain a high-quality secret image.The experimental results showed that even under destructive attacks on the container image,the proposed algorithm is successful in recovering a high-quality secret image,indicating that the algorithm exhibits a high degree of robustness against various attacks.The proposed algorithm effectively addresses the robustness issue by incorporating both spatial and channel attention mechanisms in the multi-scale wavelet domain,making it suitable for practical applications.In conclusion,the image hiding algorithm introduced in this study offers significant improvements in robustness compared to existing algorithms.Its ability to recover high-quality secret images even in the presence of destructive attacksmakes it an attractive option for various applications.Further research and experimentation can explore the algorithm’s performance under different scenarios and expand its potential applications.展开更多
Conservative chaotic systems have unique advantages over dissipative chaotic systems in the fields of secure communication and pseudo-random number generator because they do not have attractors but possess good traver...Conservative chaotic systems have unique advantages over dissipative chaotic systems in the fields of secure communication and pseudo-random number generator because they do not have attractors but possess good traversal and pseudorandomness. In this work, a novel five-dimensional(5D) Hamiltonian conservative hyperchaotic system is proposed based on the 5D Euler equation. The proposed system can have different types of coordinate transformations and time reversal symmetries. In this work, Hamilton energy and Casimir energy are analyzed firstly, and it is proved that the new system satisfies Hamilton energy conservation and can generate chaos. Then, the complex dynamic characteristics of the system are demonstrated and the conservatism and chaos characteristics of the system are verified through the correlation analysis methods such as phase diagram, equilibrium point, Lyapunov exponent, bifurcation diagram, and SE complexity. In addition, a detailed analysis of the multistable characteristics of the system reveals that many energy-related coexisting orbits exist. Based on the infinite number of center-type and saddle-type equilibrium points, the dynamic characteristics of the hidden multistability of the system are revealed. Then, the National Institute of Standards and Technology(NIST)test of the new system shows that the chaotic sequence generated by the system has strong pseudo-random. Finally, the circuit simulation and hardware circuit experiment of the system are carried out with Multisim simulation software and digital signal processor(DSP) respectively. The experimental results confirm that the new system has good ergodicity and realizability.展开更多
Image steganography is one of the prominent technologies in data hiding standards.Steganographic system performance mostly depends on the embedding strategy.Its goal is to embed strictly confidential information into ...Image steganography is one of the prominent technologies in data hiding standards.Steganographic system performance mostly depends on the embedding strategy.Its goal is to embed strictly confidential information into images without causing perceptible changes in the original image.The randomization strategies in data embedding techniques may utilize random domains,pixels,or region-of-interest for concealing secrets into a cover image,preventing information from being discovered by an attacker.The implementation of an appropriate embedding technique can achieve a fair balance between embedding capability and stego image imperceptibility,but it is challenging.A systematic approach is used with a standard methodology to carry out this study.This review concentrates on the critical examination of several embedding strategies,incorporating experimental results with state-of-the-art methods emphasizing the robustness,security,payload capacity,and visual quality metrics of the stego images.The fundamental ideas of steganography are presented in this work,along with a unique viewpoint that sets it apart from previous works by highlighting research gaps,important problems,and difficulties.Additionally,it offers a discussion of suggested directions for future study to advance and investigate uncharted territory in image steganography.展开更多
Recently,deep image-hiding techniques have attracted considerable attention in covert communication and high-capacity information hiding.However,these approaches have some limitations.For example,a cover image lacks s...Recently,deep image-hiding techniques have attracted considerable attention in covert communication and high-capacity information hiding.However,these approaches have some limitations.For example,a cover image lacks self-adaptability,information leakage,or weak concealment.To address these issues,this study proposes a universal and adaptable image-hiding method.First,a domain attention mechanism is designed by combining the Atrous convolution,which makes better use of the relationship between the secret image domain and the cover image domain.Second,to improve perceived human similarity,perceptual loss is incorporated into the training process.The experimental results are promising,with the proposed method achieving an average pixel discrepancy(APD)of 1.83 and a peak signal-to-noise ratio(PSNR)value of 40.72 dB between the cover and stego images,indicative of its high-quality output.Furthermore,the structural similarity index measure(SSIM)reaches 0.985 while the learned perceptual image patch similarity(LPIPS)remarkably registers at 0.0001.Moreover,self-testing and cross-experiments demonstrate the model’s adaptability and generalization in unknown hidden spaces,making it suitable for diverse computer vision tasks.展开更多
Traditional information hiding techniques achieve information hiding by modifying carrier data,which can easily leave detectable traces that may be detected by steganalysis tools.Especially in image transmission,both ...Traditional information hiding techniques achieve information hiding by modifying carrier data,which can easily leave detectable traces that may be detected by steganalysis tools.Especially in image transmission,both geometric and non-geometric attacks can cause subtle changes in the pixels of the image during transmission.To overcome these challenges,we propose a constructive robust image steganography technique based on style transformation.Unlike traditional steganography,our algorithm does not involve any direct modifications to the carrier data.In this study,we constructed a mapping dictionary by setting the correspondence between binary codes and image categories and then used the mapping dictionary to map secret information to secret images.Through image semantic segmentation and style transfer techniques,we combined the style of secret images with the content of public images to generate stego images.This type of stego image can resist interference during public channel transmission,ensuring the secure transmission of information.At the receiving end,we input the stego image into a trained secret image reconstruction network,which can effectively reconstruct the original secret image and further recover the secret information through a mapping dictionary to ensure the security,accuracy,and efficient decoding of the information.The experimental results show that this constructive information hiding method based on style transfer improves the security of information hiding,enhances the robustness of the algorithm to various attacks,and ensures information security.展开更多
The act of transmitting photos via the Internet has become a routine and significant activity.Enhancing the security measures to safeguard these images from counterfeiting and modifications is a critical domain that c...The act of transmitting photos via the Internet has become a routine and significant activity.Enhancing the security measures to safeguard these images from counterfeiting and modifications is a critical domain that can still be further enhanced.This study presents a system that employs a range of approaches and algorithms to ensure the security of transmitted venous images.The main goal of this work is to create a very effective system for compressing individual biometrics in order to improve the overall accuracy and security of digital photographs by means of image compression.This paper introduces a content-based image authentication mechanism that is suitable for usage across an untrusted network and resistant to data loss during transmission.By employing scale attributes and a key-dependent parametric Long Short-Term Memory(LSTM),it is feasible to improve the resilience of digital signatures against image deterioration and strengthen their security against malicious actions.Furthermore,the successful implementation of transmitting biometric data in a compressed format over a wireless network has been accomplished.For applications involving the transmission and sharing of images across a network.The suggested technique utilizes the scalability of a structural digital signature to attain a satisfactory equilibrium between security and picture transfer.An effective adaptive compression strategy was created to lengthen the overall lifetime of the network by sharing the processing of responsibilities.This scheme ensures a large reduction in computational and energy requirements while minimizing image quality loss.This approach employs multi-scale characteristics to improve the resistance of signatures against image deterioration.The proposed system attained a Gaussian noise value of 98%and a rotation accuracy surpassing 99%.展开更多
基金Supported by the Scientific Research Project of Hebei Entry-Exit Inspection and Quarantine Bureau(HE2013K030)~~
文摘The situation of intercepted alien pests from imported hides in Hebei during 2013-2014 was systematically analyzed. The results showed that 163 batches of alien pests were intercepted, including 2 batches of quarantine weeds and they both were Italian cocklebur. According to the statistics of original countries, the intercepted hides from 21 countries all had alien pests, in which Australia was the largest number of batches and species of alien pests. The analysis results showed that there was severe risk in the imported hides carrying alien pests, thus to effectively prevent the invasion of alien pests to our country, several quarantine measures should be taken in the future, such as enhancing the quarantine inspection in ports, and promoting the personnel ability of interception and species identification of alien pests.
文摘A category of chromium (Cr)-containing fertilizers is represented by the fertilizers deriving from byproducts of tanning process. Their use is widespread because of their good agronomic response due to the high content of slow release or- ganic nitrogen (N) and carbon (C). They do not represent an environmental hazard because only the non-toxic form of Cr(III) is present. Productive processes may involve chemical, enzymatic or thermal hydrolysis. The final product is characterized by different contents of peptides and free amino acids depending on the type of hydrolysis. Legislation concerning Cr-containing fertilizers is controversial because often do not consider any scientific evidences;nevertheless, the European Union, the United States and countries as Italy, do not set the restriction to Cr(III) and generally only the presence of the toxic form, Cr(VI), is limited. Depending on its two main oxidation forms, Cr issue has been studied for many years. Several authors confirmed that Cr(VI) is carcinogenic, while Cr(III) is an essential trace element in human and animal diet. In soil Cr(III) has low mobility, whereas Cr(VI) is highly water soluble. However Cr(VI) in soil is quickly reduced to Cr(III);on the contrary oxidation of Cr(III) to Cr(VI) is rarely possible because particular conditions must occur. Only a very small fraction of Cr in soil is available to plant uptake and its translocation in edible parts is limited because it is immobilized in roots as Cr(III). Therefore risks of environmental pollution using these fertilizers are negligible;on the contrary they have positive environmental and agronomical effects. The aim of this review is to deal with the category of the organic fertilizers containing Cr derived from tannery processes focusing on its chemical, productive, legislative, environmental and agronomical aspects. Special attention is given to the ambiguous issue of Cr briefly summarizing the most important studies of the last forty years.
文摘Data hiding methods involve embedding secret messages into cover objects to enable covert communication in a way that is difficult to detect.In data hiding methods based on image interpolation,the image size is reduced and then enlarged through interpolation,followed by the embedding of secret data into the newly generated pixels.A general improving approach for embedding secret messages is proposed.The approach may be regarded a general model for enhancing the data embedding capacity of various existing image interpolation-based data hiding methods.This enhancement is achieved by expanding the range of pixel values available for embedding secret messages,removing the limitations of many existing methods,where the range is restricted to powers of two to facilitate the direct embedding of bit-based messages.This improvement is accomplished through the application of multiple-based number conversion to the secret message data.The method converts the message bits into a multiple-based number and uses an algorithm to embed each digit of this number into an individual pixel,thereby enhancing the message embedding efficiency,as proved by a theorem derived in this study.The proposed improvement method has been tested through experiments on three well-known image interpolation-based data hiding methods.The results show that the proposed method can enhance the three data embedding rates by approximately 14%,13%,and 10%,respectively,create stego-images with good quality,and resist RS steganalysis attacks.These experimental results indicate that the use of the multiple-based number conversion technique to improve the three interpolation-based methods for embedding secret messages increases the number of message bits embedded in the images.For many image interpolation-based data hiding methods,which use power-of-two pixel-value ranges for message embedding,other than the three tested ones,the proposed improvement method is also expected to be effective for enhancing their data embedding capabilities.
基金supported in part by the National Natural Science Foundation of China(Nos.62202234,62401270)the China Postdoctoral Science Foundation(No.2023M741778)the Natural Science Foundation of Jiangsu Province(Nos.BK20240706,BK20240694).
文摘Generative image steganography is a technique that directly generates stego images from secret infor-mation.Unlike traditional methods,it theoretically resists steganalysis because there is no cover image.Currently,the existing generative image steganography methods generally have good steganography performance,but there is still potential room for enhancing both the quality of stego images and the accuracy of secret information extraction.Therefore,this paper proposes a generative image steganography algorithm based on attribute feature transformation and invertible mapping rule.Firstly,the reference image is disentangled by a content and an attribute encoder to obtain content features and attribute features,respectively.Then,a mean mapping rule is introduced to map the binary secret information into a noise vector,conforming to the distribution of attribute features.This noise vector is input into the generator to produce the attribute transformed stego image with the content feature of the reference image.Additionally,we design an adversarial loss,a reconstruction loss,and an image diversity loss to train the proposed model.Experimental results demonstrate that the stego images generated by the proposed method are of high quality,with an average extraction accuracy of 99.4%for the hidden information.Furthermore,since the stego image has a uniform distribution similar to the attribute-transformed image without secret information,it effectively resists both subjective and objective steganalysis.
文摘One sunny day,a little dog with the name Max met a little cat named Lily in the backyard.Max:Hi,Lily!I'm looking for something interesting to do.Do you want to play with me?Lily:Sure,Max!But how 1 can we play?Max:How about hide-and-seek?Lily:Sound②great!You count first,and I'll go hide.
文摘Establish an efficacy evaluation method for foundation products in vivo and vitro.The hiding power,whiteness,waterproof and anti-sweat effect were evaluated in vitro test,where CR ratio,Individual Type Angle (ITA°) and chromatic aberration (E) were measured as evaluation indicators by standard black/white cardboard,artificial leather and artificial sweat.In clinical assessment,the anti-stain,waterproof,anti-sweat effect of the foundation products were evaluated through the ΔE change,before and after the treatment of products by staining,wetting,sweating in forearm skin.There were significant differences in CR ratio of different types of samples on standard black and white cardboards (P<0.05),ITA° of artificial leather has a significant increase after treatment (P<0.05),?E﹤1.5 in black cloth after dipping test,while ΔE﹤1.5 in leather after water and artificial sweat treatment.Clinical assessment showed that ?E ﹤50%,which had no significant difference in human skin color,before and after the test (P>0.05).The change trend of efficacy evaluation in vitro test was basically consistent with that of visual evaluation and clinical assessment,indicated that the efficacy evaluation methods of foundation products in vivo and vitro are intuitive,quantifiable,and can be used to evaluate the efficacy of foundation products.
基金supported in part by the National Key R&D Program of China(Grant No.2019YFB2101700)the National Natural Science Foundation of China(Grant No.62272102,No.62172320,No.U21A20466)+4 种基金the Open Research Fund of Key Laboratory of Cryptography of Zhejiang Province(Grant No.ZCL21015)the Qinghai Key R&D and Transformation Projects(Grant No.2021-GX-112)the Natural Science Foundation of Nanjing University of Posts and Telecommunications(Grant No.NY222141)the Natural Science Foundation of Jiangsu Higher Education Institutions of China under Grant(No.22KJB520029)Henan Key Laboratory of Network Cryptography Technology(No.LNCT2022-A10)。
文摘Ciphertext-Policy Attribute-Based Encryption(CP-ABE)enables fine-grained access control on ciphertexts,making it a promising approach for managing data stored in the cloud-enabled Internet of Things.But existing schemes often suffer from privacy breaches due to explicit attachment of access policies or partial hiding of critical attribute content.Additionally,resource-constrained IoT devices,especially those adopting wireless communication,frequently encounter affordability issues regarding decryption costs.In this paper,we propose an efficient and fine-grained access control scheme with fully hidden policies(named FHAC).FHAC conceals all attributes in the policy and utilizes bloom filters to efficiently locate them.A test phase before decryption is applied to assist authorized users in finding matches between their attributes and the access policy.Dictionary attacks are thwarted by providing unauthorized users with invalid values.The heavy computational overhead of both the test phase and most of the decryption phase is outsourced to two cloud servers.Additionally,users can verify the correctness of multiple outsourced decryption results simultaneously.Security analysis and performance comparisons demonstrate FHAC's effectiveness in protecting policy privacy and achieving efficient decryption.
基金funded by theNational Science and Technology Council of Taiwan under the grant number NSTC 113-2221-E-035-058.
文摘With the rapid expansion of multimedia data,protecting digital information has become increasingly critical.Reversible data hiding offers an effective solution by allowing sensitive information to be embedded in multimedia files while enabling full recovery of the original data after extraction.Audio,as a vital medium in communication,entertainment,and information sharing,demands the same level of security as images.However,embedding data in encrypted audio poses unique challenges due to the trade-offs between security,data integrity,and embedding capacity.This paper presents a novel interpolation-based reversible data hiding algorithm for encrypted audio that achieves scalable embedding capacity.By increasing sample density through interpolation,embedding opportunities are significantly enhanced while maintaining encryption throughout the process.The method further integrates multiple most significant bit(multi-MSB)prediction and Huffman coding to optimize compression and embedding efficiency.Experimental results on standard audio datasets demonstrate the proposed algorithm’s ability to embed up to 12.47 bits per sample with over 9.26 bits per sample available for pure embedding capacity,while preserving full reversibility.These results confirm the method’s suitability for secure applications that demand high embedding capacity and perfect reconstruction of original audio.This work advances reversible data hiding in encrypted audio by offering a secure,efficient,and fully reversible data hiding framework.
文摘This study introduces an Edge-Based Data Hiding and Extraction Algorithm(EBDHEA)to address the problem of data embedding in images while preserving robust security and high image quality.The algorithm produces three classes of pixels from the pixels in the cover image:edges found by the Canny edge detection method,pixels arising from the expansion of neighboring edge pixels,and pixels that are neither edges nor components of the neighboring edge pixels.The number of Least Significant Bits(LSBs)that are used to hide data depends on these classifications.Furthermore,the lossless compression method,Huffman coding,improves image data capacity.To increase the security of the steganographic process,secret messages are encrypted using the XOR encryption technique before being embedded.Metrics such as the Mean Squared Error(MSE),Peak Signal-to-Noise Ratio(PSNR),and Structural Similarity Index Measure(SSIM)are used to assess the efficacy of this algorithm and are compared to previous methods.The findings demonstrate that the suggested approach achieves high similarity between the original and modified images with a maximum PSNR of 60.7 dB for a payload of 18,750 bytes,a maximum SSIM of 0.999 for a payload of 314,572.8 bytes,and a maximum Video Information Fidelity(VIF)of 0.95 for a payload of 23,592 bytes.Normalized Cross-Correlation(NCC)values are very close to 1.In addition,the performance of EBDHEA is implemented on Secure Medical Image Transmission as a real-world example,and the performance is tested against three types of attacks:RS Steganalysis,Chi-square attack,and visual attack,and compared with two deep learning models,such as SRNet and XuNet.
基金supported by the Social Science Foundation of Liaoning Province(L23BJY022).
文摘We explored the effects of algorithmic opacity on employees’playing dumb and evasive hiding rather than rationalized hiding.We examined the mediating role of job insecurity and the moderating role of employee-AI collaboration.Participants were 421 full-time employees(female=46.32%,junior employees=31.83%)from a variety of organizations and industries that interact with AI.Employees filled out data on algorithm opacity,job insecurity,knowledge hiding,employee-AI collaboration,and control variables.The results of the structural equation modeling indicated that algorithm opacity exacerbated employees’job insecurity,and job insecurity mediated between algorithm opacity and playing dumb and evasive hiding rather than rationalized hiding.The relationship between algorithmic opacity and playing dumb and evasive hiding was more positive when the level of employee-AI collaboration was higher.These findings suggest that employee-AI collaboration reinforces the indirect relationship between algorithmic opacity and playing dumb and evasive hiding.Our study contributes to research on human and AI collaboration by exploring the dark side of employee-AI collaboration.
基金supported in part by the National Natural Science Foundation of China under Grants 62102450,62272478the Independent Research Project of a Certain Unit under Grant ZZKY20243127.
文摘Federated Learning(FL)has emerged as a promising distributed machine learning paradigm that enables multi-party collaborative training while eliminating the need for raw data sharing.However,its reliance on a server introduces critical security vulnerabilities:malicious servers can infer private information from received local model updates or deliberately manipulate aggregation results.Consequently,achieving verifiable aggregation without compromising client privacy remains a critical challenge.To address these problem,we propose a reversible data hiding in encrypted domains(RDHED)scheme,which designs joint secret message embedding and extraction mechanism.This approach enables clients to embed secret messages into ciphertext redundancy spaces generated during model encryption.During the server aggregation process,the embedded messages from all clients fuse within the ciphertext space to form a joint embedding message.Subsequently,clients can decrypt the aggregated results and extract this joint embedding message for verification purposes.Building upon this foundation,we integrate the proposed RDHED scheme with linear homomorphic hash and digital signatures to design a verifiable privacy-preserving aggregation protocol for single-server architectures(VPAFL).Theoretical proofs and experimental analyses show that VPAFL can effectively protect user privacy,achieve lightweight computational and communication overhead of users for verification,and present significant advantages with increasing model dimension.
基金supported by the National Natural Science Foundation of China(Grant Nos.62072250,61772281,61702235,U1636117,U1804263,62172435,61872203 and 61802212)the Zhongyuan Science and Technology Innovation Leading Talent Project of China(Grant No.214200510019)+3 种基金the Suqian Municipal Science and Technology Plan Project in 2020(S202015)the Plan for Scientific Talent of Henan Province(Grant No.2018JR0018)the Opening Project of Guangdong Provincial Key Laboratory of Information Security Technology(Grant No.2020B1212060078)the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)Fund.
文摘Medical image segmentation,i.e.,labeling structures of interest in medical images,is crucial for disease diagnosis and treatment in radiology.In reversible data hiding in medical images(RDHMI),segmentation consists of only two regions:the focal and nonfocal regions.The focal region mainly contains information for diagnosis,while the nonfocal region serves as the monochrome background.The current traditional segmentation methods utilized in RDHMI are inaccurate for complex medical images,and manual segmentation is time-consuming,poorly reproducible,and operator-dependent.Implementing state-of-the-art deep learning(DL)models will facilitate key benefits,but the lack of domain-specific labels for existing medical datasets makes it impossible.To address this problem,this study provides labels of existing medical datasets based on a hybrid segmentation approach to facilitate the implementation of DL segmentation models in this domain.First,an initial segmentation based on a 33 kernel is performed to analyze×identified contour pixels before classifying pixels into focal and nonfocal regions.Then,several human expert raters evaluate and classify the generated labels into accurate and inaccurate labels.The inaccurate labels undergo manual segmentation by medical practitioners and are scored based on a hierarchical voting scheme before being assigned to the proposed dataset.To ensure reliability and integrity in the proposed dataset,we evaluate the accurate automated labels with manually segmented labels by medical practitioners using five assessment metrics:dice coefficient,Jaccard index,precision,recall,and accuracy.The experimental results show labels in the proposed dataset are consistent with the subjective judgment of human experts,with an average accuracy score of 94%and dice coefficient scores between 90%-99%.The study further proposes a ResNet-UNet with concatenated spatial and channel squeeze and excitation(scSE)architecture for semantic segmentation to validate and illustrate the usefulness of the proposed dataset.The results demonstrate the superior performance of the proposed architecture in accurately separating the focal and nonfocal regions compared to state-of-the-art architectures.Dataset information is released under the following URL:https://www.kaggle.com/lordamoah/datasets(accessed on 31 March 2025).
基金the National Natural Science Foundation of China(Nos.62272478,61872384)Natural Science Foundation of Shanxi Province(No.2023-JC-YB-584)+1 种基金National Natural Science Foundation of China(No.62172436)Engineering University of PAP’s Funding for Scientific Research Innovation Team,Engineering University of PAP’s Funding for Key Researcher(No.KYGG202011).
文摘This paper proposes an artificial intelligence-based robust information hiding algorithm to address the issue of confidential information being susceptible to noise attacks during transmission.The algorithm we designed aims to mitigate the impact of various noise attacks on the integrity of secret information during transmission.The method we propose involves encoding secret images into stylized encrypted images and applies adversarial transfer to both the style and content features of the original and embedded data.This process effectively enhances the concealment and imperceptibility of confidential information,thereby improving the security of such information during transmission and reducing security risks.Furthermore,we have designed a specialized attack layer to simulate real-world attacks and common noise scenarios encountered in practical environments.Through adversarial training,the algorithm is strengthened to enhance its resilience against attacks and overall robustness,ensuring better protection against potential threats.Experimental results demonstrate that our proposed algorithm successfully enhances the concealment and unknowability of secret information while maintaining embedding capacity.Additionally,it ensures the quality and fidelity of the stego image.The method we propose not only improves the security and robustness of information hiding technology but also holds practical application value in protecting sensitive data and ensuring the invisibility of confidential information.
基金supported by the National Key Research and Development Program of China(No.2022YFB3102900)the National Natural Science Foundation of China(Nos.62172435,62202495 and 62002103)+2 种基金Zhongyuan Science and Technology Innovation Leading Talent Project of China(No.214200510019)Key Research and Development Project of Henan Province(No.2211321200)the Natural Science Foundation of Henan Province(No.222300420058).
文摘The rapid development of the internet and digital media has provided convenience while also posing a potential risk of steganography abuse.Identifying steganographer is essential in tracing secret information origins and preventing illicit covert communication online.Accurately discerning a steganographer from many normal users is challenging due to various factors,such as the complexity in obtaining the steganography algorithm,extracting highly separability features,and modeling the cover data.After extensive exploration,several methods have been proposed for steganographer identification.This paper presents a survey of existing studies.Firstly,we provide a concise introduction to the research background and outline the issue of steganographer identification.Secondly,we present fundamental concepts and techniques that establish a general framework for identifying steganographers.Within this framework,state-of-the-art methods are summarized from five key aspects:data acquisition,feature extraction,feature optimization,identification paradigm,and performance evaluation.Furthermore,theoretical and experimental analyses examine the advantages and limitations of these existing methods.Finally,the survey highlights outstanding issues in image steganographer identification that deserve further research.
基金partly supported by the National Natural Science Foundation of China(Jianhua Wu,Grant No.62041106).
文摘Hidden capacity,concealment,security,and robustness are essential indicators of hiding algorithms.Currently,hiding algorithms tend to focus on algorithmic capacity,concealment,and security but often overlook the robustness of the algorithms.In practical applications,the container can suffer from damage caused by noise,cropping,and other attacks during transmission,resulting in challenging or even impossible complete recovery of the secret image.An image hiding algorithm based on dynamic region attention in the multi-scale wavelet domain is proposed to address this issue and enhance the robustness of hiding algorithms.In this proposed algorithm,a secret image of size 256×256 is first decomposed using an eight-level Haar wavelet transform.The wavelet transform generates one coefficient in the approximation component and twenty-four detail bands,which are then embedded into the carrier image via a hiding network.During the recovery process,the container image is divided into four non-overlapping parts,each employed to reconstruct a low-resolution secret image.These lowresolution secret images are combined using densemodules to obtain a high-quality secret image.The experimental results showed that even under destructive attacks on the container image,the proposed algorithm is successful in recovering a high-quality secret image,indicating that the algorithm exhibits a high degree of robustness against various attacks.The proposed algorithm effectively addresses the robustness issue by incorporating both spatial and channel attention mechanisms in the multi-scale wavelet domain,making it suitable for practical applications.In conclusion,the image hiding algorithm introduced in this study offers significant improvements in robustness compared to existing algorithms.Its ability to recover high-quality secret images even in the presence of destructive attacksmakes it an attractive option for various applications.Further research and experimentation can explore the algorithm’s performance under different scenarios and expand its potential applications.
基金Project supported by the Heilongjiang Province Natural Science Foundation Joint Guidance Project,China (Grant No.LH2020F022)the Fundamental Research Funds for the Central Universities,China (Grant No.3072022CF0801)。
文摘Conservative chaotic systems have unique advantages over dissipative chaotic systems in the fields of secure communication and pseudo-random number generator because they do not have attractors but possess good traversal and pseudorandomness. In this work, a novel five-dimensional(5D) Hamiltonian conservative hyperchaotic system is proposed based on the 5D Euler equation. The proposed system can have different types of coordinate transformations and time reversal symmetries. In this work, Hamilton energy and Casimir energy are analyzed firstly, and it is proved that the new system satisfies Hamilton energy conservation and can generate chaos. Then, the complex dynamic characteristics of the system are demonstrated and the conservatism and chaos characteristics of the system are verified through the correlation analysis methods such as phase diagram, equilibrium point, Lyapunov exponent, bifurcation diagram, and SE complexity. In addition, a detailed analysis of the multistable characteristics of the system reveals that many energy-related coexisting orbits exist. Based on the infinite number of center-type and saddle-type equilibrium points, the dynamic characteristics of the hidden multistability of the system are revealed. Then, the National Institute of Standards and Technology(NIST)test of the new system shows that the chaotic sequence generated by the system has strong pseudo-random. Finally, the circuit simulation and hardware circuit experiment of the system are carried out with Multisim simulation software and digital signal processor(DSP) respectively. The experimental results confirm that the new system has good ergodicity and realizability.
基金This research was funded by the Ministry of Higher Education(MOHE)through Fundamental Research Grant Scheme(FRGS)under the Grand Number FRGS/1/2020/ICT01/UK M/02/4,and University Kebangsaan Malaysia for open access publication.
文摘Image steganography is one of the prominent technologies in data hiding standards.Steganographic system performance mostly depends on the embedding strategy.Its goal is to embed strictly confidential information into images without causing perceptible changes in the original image.The randomization strategies in data embedding techniques may utilize random domains,pixels,or region-of-interest for concealing secrets into a cover image,preventing information from being discovered by an attacker.The implementation of an appropriate embedding technique can achieve a fair balance between embedding capability and stego image imperceptibility,but it is challenging.A systematic approach is used with a standard methodology to carry out this study.This review concentrates on the critical examination of several embedding strategies,incorporating experimental results with state-of-the-art methods emphasizing the robustness,security,payload capacity,and visual quality metrics of the stego images.The fundamental ideas of steganography are presented in this work,along with a unique viewpoint that sets it apart from previous works by highlighting research gaps,important problems,and difficulties.Additionally,it offers a discussion of suggested directions for future study to advance and investigate uncharted territory in image steganography.
基金supported by the National Key R&D Program of China(Grant Number 2021YFB2700900)the National Natural Science Foundation of China(Grant Numbers 62172232,62172233)the Jiangsu Basic Research Program Natural Science Foundation(Grant Number BK20200039).
文摘Recently,deep image-hiding techniques have attracted considerable attention in covert communication and high-capacity information hiding.However,these approaches have some limitations.For example,a cover image lacks self-adaptability,information leakage,or weak concealment.To address these issues,this study proposes a universal and adaptable image-hiding method.First,a domain attention mechanism is designed by combining the Atrous convolution,which makes better use of the relationship between the secret image domain and the cover image domain.Second,to improve perceived human similarity,perceptual loss is incorporated into the training process.The experimental results are promising,with the proposed method achieving an average pixel discrepancy(APD)of 1.83 and a peak signal-to-noise ratio(PSNR)value of 40.72 dB between the cover and stego images,indicative of its high-quality output.Furthermore,the structural similarity index measure(SSIM)reaches 0.985 while the learned perceptual image patch similarity(LPIPS)remarkably registers at 0.0001.Moreover,self-testing and cross-experiments demonstrate the model’s adaptability and generalization in unknown hidden spaces,making it suitable for diverse computer vision tasks.
基金the National Natural Science Foundation of China(Nos.62272478,61872384,62172436,62102451)Natural Science Foundation of Shanxi Province(No.2023-JC-YB-584)Engineering University of PAP’s Funding for Key Researcher(No.KYGG202011).
文摘Traditional information hiding techniques achieve information hiding by modifying carrier data,which can easily leave detectable traces that may be detected by steganalysis tools.Especially in image transmission,both geometric and non-geometric attacks can cause subtle changes in the pixels of the image during transmission.To overcome these challenges,we propose a constructive robust image steganography technique based on style transformation.Unlike traditional steganography,our algorithm does not involve any direct modifications to the carrier data.In this study,we constructed a mapping dictionary by setting the correspondence between binary codes and image categories and then used the mapping dictionary to map secret information to secret images.Through image semantic segmentation and style transfer techniques,we combined the style of secret images with the content of public images to generate stego images.This type of stego image can resist interference during public channel transmission,ensuring the secure transmission of information.At the receiving end,we input the stego image into a trained secret image reconstruction network,which can effectively reconstruct the original secret image and further recover the secret information through a mapping dictionary to ensure the security,accuracy,and efficient decoding of the information.The experimental results show that this constructive information hiding method based on style transfer improves the security of information hiding,enhances the robustness of the algorithm to various attacks,and ensures information security.
文摘The act of transmitting photos via the Internet has become a routine and significant activity.Enhancing the security measures to safeguard these images from counterfeiting and modifications is a critical domain that can still be further enhanced.This study presents a system that employs a range of approaches and algorithms to ensure the security of transmitted venous images.The main goal of this work is to create a very effective system for compressing individual biometrics in order to improve the overall accuracy and security of digital photographs by means of image compression.This paper introduces a content-based image authentication mechanism that is suitable for usage across an untrusted network and resistant to data loss during transmission.By employing scale attributes and a key-dependent parametric Long Short-Term Memory(LSTM),it is feasible to improve the resilience of digital signatures against image deterioration and strengthen their security against malicious actions.Furthermore,the successful implementation of transmitting biometric data in a compressed format over a wireless network has been accomplished.For applications involving the transmission and sharing of images across a network.The suggested technique utilizes the scalability of a structural digital signature to attain a satisfactory equilibrium between security and picture transfer.An effective adaptive compression strategy was created to lengthen the overall lifetime of the network by sharing the processing of responsibilities.This scheme ensures a large reduction in computational and energy requirements while minimizing image quality loss.This approach employs multi-scale characteristics to improve the resistance of signatures against image deterioration.The proposed system attained a Gaussian noise value of 98%and a rotation accuracy surpassing 99%.
