Sensing Data Concealment in NFTs: A Steganographic Model for Confidential Cross-Border Information Exchange

In an era dominated by rapid digitalization of sensed data, the secure exchange of sensitive information poses a critical challenge across various sectors. Established techniques, particularly in emerging technologies like the Internet of Things (IoT), grapple with inherent risks in ensuring data confidentiality, integrity, and vulnerabilities to evolving cyber threats. Blockchain technology, known for its decentralized and tamper-resistant characteristics, stands as a reliable solution for secure data exchange. However, the persistent challenge lies in protecting sensitive information amidst evolving digital landscapes. Among the burgeoning applications of blockchain technology, non-fungible tokens (NFTs) have emerged as digital certificates of ownership, securely recording various types of data on a distributed ledger. Unlike traditional data storage methods, NFTs offer several advantages for secure information exchange. Firstly, their tamperproof nature guarantees the authenticity and integrity of the data. Secondly, NFTs can hold both immutable and mutable data within the same token, simplifying management and access control. Moving beyond their conventional association with art and collectibles, this paper presents a novel approach that utilizes NFTs as dynamic carriers for sensitive information. Our solution leverages the immutable NFT data to serve as a secure data pointer, while the mutable NFT data holds sensitive information protected by steganography. Steganography embeds the data within the NFT, making them invisible to unauthorized eyes, while facilitating portability. This dual approach ensures both data integrity and authorized access, even in the face of evolving digital threats. A performance analysis confirms the approach's effectiveness, demonstrating its reliability, robustness, and resilience against attacks on hidden data. This paves the way for secure data transmission across diverse industries.

Covert Communication through Robust Fragment Hiding in a Large Number of Images

For covert communication in lossy channels, it is necessary to consider that the carrier of the hidden watermark will undergo multiple image-processing attacks. In order to ensure that secret information can be extracted without distortion from the watermarked images that have undergone attacks, in this paper, we design a novel fragmented secure communication system. The sender will fragment the secret data to be transmitted and redundantly hide it in a large number of multimodal carriers of messenger accounts on multiple social platforms. The receiver receives enough covert carriers, extracts each fragment, and concatenates the transmitted secret data. This article uses the image carrier as an example to fragment the text file intended for transmission and embeds it into a large number of images, with each fragment being redundant and embedded into multiple images. In this way, at the receiving end, only enough stego images need to be received to extract the information in each image, and then concatenate the final secret file. In order to resist various possible attacks during image transmission, we propose a strong robust image watermarking method. This method adopts a watermark layer based on DFT, which has high embedding and detection efficiency and good invisibility. Secondly, a watermark layer based on DCT is adopted, which can resist translation attacks, JPEG attacks, and other common attacks. Experiments have shown that our watermarking method is very fast; both the embedding time and the extraction time are less than 0.15 s for images not larger than 2000×2000. Our watermarking method has very good invisibility with 41dB PSNR on average. And our watermarking method is more robust than existing schemes and robust to nearly all kinds of attacks. Based on this strong robust image watermarking method, the scheme of fragmenting and hiding redundant transmission content into a large number of images is effective and practical. Our scheme can 100% restore the secret file completely under different RST or hybrid attacks, such as rotation by 1 degree and 5 degrees, scaling by 1.25 and 0.8, and cropping by 10% and 25%. Our scheme can successfully restore the secret file completely even if 30% of received images are lost. When 80% of received images are lost, our scheme can still restore 61.1% of the secret file. If all stego images can be obtained, the original text file can be completely restored.

Creating Digital Watermarks in Bitmap Images Using Lagrange Interpolation and Bezier Curves

The article is devoted to the introduction of digital watermarks, which formthe basis for copyright protection systems. Methods in this area are aimed at embedding hidden markers that are resistant to various container transformations. This paper proposes a method for embedding a digital watermark into bitmap images using Lagrange interpolation and the Bezier curve formula for five points, called Lagrange interpolation along the Bezier curve 5 (LIBC5). As a means of steganalysis, the RS method was used, which uses a sensitive method of double statistics obtained on the basis of spatial correlations in images. The output value of the RS analysis is the estimated length of the message in the image under study. The stability of the developed LIBC5 method to the detection of message transmission by the RS method has been experimentally determined. The developed method proved to be resistant to RS analysis. A study of the LIBC5 method showed an improvement in quilting resistance compared to that of the INMI image embedding method, which also uses Lagrange interpolation. Thus, the LIBC5 stegosystem can be successfully used to protect confidential data and copyrights.

Hiding Information in Digital Images Using Ant Algorithms

Stenographic methods are closely related to the security and confidentiality of communications, which have always been essential domains of human life. Steganography itself is a science dedicated to the process of hiding information in public communication channels. Its main idea is to use digital files or even communication protocols as a medium inside which data are hidden. The present research aims to investigate the applicability of ant algorithms in steganography and evaluate the effectiveness of this approach. Ant systems could be employed both in spatial and frequency-based image steganography. The combination of frequency domain and optimization method to increase robustness is used, and an integer wavelet transform is performed on the host image. ACO optimization is used to find the optimal coefficients describing where to hide the data. The other method utilizes ACO to determine the optimal pixel locations for embedding secret data in the cover image. ACO is also used to detect complex regions of the cover image. Afterward, the least-significant-bits (LSB) substitution is used to hide secret information in the detected complex regions' pixels. Our study focuses on optimizing two mutually exclusive features of steganograms-high capacity and low distortion. An attempt was made to use ant systems to select areas of digital images that allow the greatest amount of information to be hidden with the least loss of image quality. The effect of variants of the ant system and its parameters on the quality of the results obtained was also investigated, and the final effectiveness of the proposed method was evaluated. The results of the experiments were compared with those published in related articles. The proposed procedures proved to be effective and allowed the embedding of large amounts of data with relatively little impact on image quality.

A Novel Steganography Method for Infrared Image Based on Smooth Wavelet Transform and Convolutional Neural Network

Infrared images have been widely used in many research areas, such as target detection and scene monitoring. Therefore, the copyright protection of infrared images is very important. In order to accomplish the goal of image-copyright protection, a large number of image-steganography algorithms have been studied in the last two decades. Most of the existing image-steganography algorithms hide information based on the prediction error of pixels. Consequently, reducing the prediction error of pixels is very important for steganography algorithms. In this paper, we propose a novel framework SSCNNP: a Convolutional Neural-Network Predictor (CNNP) based on Smooth-Wavelet Transform (SWT) and Squeeze-Excitation (SE) attention for infrared image prediction, which combines Convolutional Neural Network (CNN) with SWT. Firstly, the Super-Resolution Convolutional Neural Network (SRCNN) and SWT are used for preprocessing half of the input infrared image. Then, CNNP is applied to predict the other half of the infrared image. To improve the prediction accuracy of CNNP, an attention mechanism is added to the proposed model. The experimental results demonstrate that the proposed algorithm reduces the prediction error of the pixels due to full utilization of the features around the pixel in both the spatial and the frequency domain. Moreover, the proposed model does not require either expensive equipment or a large amount of storage space during the training process. Experimental results show that the proposed algorithm had good performances in terms of imperceptibility and watermarking capacity compared with advanced steganography algorithms. The proposed algorithm improved the PSNR by 0.17 on average with the same watermark capacity.

Multiplexing Optical Images for Steganography by Single Metasurfaces

Image steganography based on intelligent devices is one of the effective routes for safely and quickly transferring secret information. However, optical image steganography has attracted far less attention than digital one due to the state-of-the-art technology limitations of high-resolution optical imaging in integrated devices. Optical metasurfaces, composed of ultrathin subwavelength meta-atoms, are extensively considered for flat optical-imaging nano-components with high-resolutions as competitive candidates for next-generation miniaturized devices. Here, multiplex imaging metasurfaces composed of single nanorods are proposed under a detailed strategy to realize optical image steganography. The simulation and experimental results demonstrate that an optical steganographic metasurface can simultaneously transfer independent secret image information to two receivers with special keys, without raising suspicions for the general public under the cloak of a cover image. The proposed optical steganographic strategy by metasurfaces can arbitrarily distribute a continuous grayscale image together with a black-and-white image in separate channels, implying the distinguishing feature of high-density information capacity for integration and miniaturization in optical meta-devices.

Steganography in IoT: Information Hiding with Joystick and Touch Sensors

This paper describes a multi-secret steganographic system for the Internet-of-Things. It uses two user-friendly sensors for data input: thumb joystick and touch sensor. These devices are not only easy to use, but also allow hidden data entry. The system conceals multiple messages into the same container, but with different algorithms. The embedding is realized with two methods of video steganography that work on mp4 files, namely, videostego and metastego. These methods were chosen because of their low complexity so that they may operate smoothly in environments with limited resources. It is possible to replace the suggested sensors with others that offer similar functionality.

Lossless Image Steganography Based on Invertible Neural Networks

Image steganography is a scheme that hides secret information in a cover image without being perceived. Most of the existing steganography methods are more concerned about the visual similarity between the stego image and the cover image, and they ignore the recovery accuracy of secret information. In this paper, the steganography method based on invertible neural networks is proposed, which can generate stego images with high invisibility and security and can achieve lossless recovery for secret information. In addition, this paper introduces a mapping module that can compress information actually embedded to improve the quality of the stego image and its antidetection ability. In order to restore message and prevent loss, the secret information is converted into a binary sequence and then embedded in the cover image through the forward operation of the invertible neural networks. This information will then be recovered from the stego image through the inverse operation of the invertible neural networks. Experimental results show that the proposed method in this paper has achieved competitive results in the visual quality and safety of stego images and achieved 100% accuracy in information extraction.

NN-Based 8FSK Demodulator for the Covert Channel

In this article, a superposition-based covert channel and its demodulator were proposed and examined. As a covert waveform, an 8FSK modulation was selected. The impact of the channel estimation error and resulting imperfect SIC operation (successive interference cancelation) on the covert information demodulation process was considered. Especially for this imperfection, an NN-based demodulator was proposed. The superiority of this solution over the traditional 8FSK correlator-based receiver was examined for various cases, including the hard- and soft-decision detectors. It was proven that, although NN does not provide BER values equal to zero, even for the perfect SIC, it generally overcomes the traditional correlator-based 8FSK demodulator. Simulation results showed that the NN-base demodulator, in the case of additional covert channel coding, provides error-free demodulation, even for four-times greater channel gain error.

A Novel Steganography Method for Character-Level Text Image Based on Adversarial Attacks

The Internet has become the main channel of information communication, which contains a large amount of secret information. Although network communication provides a convenient channel for human communication, there is also a risk of information leakage. Traditional image steganography algorithms use manually crafted steganographic algorithms or custom models for steganography, while our approach uses ordinary OCR models for information embedding and extraction. Even if our OCR models for steganography are intercepted, it is difficult to find their relevance to steganography. We propose a novel steganography method for character-level text images based on adversarial attacks. We exploit the complexity and uniqueness of neural network boundaries and use neural networks as a tool for information embedding and extraction. We use an adversarial attack to embed the steganographic information into the character region of the image. To avoid detection by other OCR models, we optimize the generation of the adversarial samples and use a verification model to filter the generated steganographic images, which, in turn, ensures that the embedded information can only be recognized by our local model. The decoupling experiments show that the strategies we adopt to weaken the transferability can reduce the possibility of other OCR models recognizing the embedded information while ensuring the success rate of information embedding. Meanwhile, the perturbations we add to embed the information are acceptable. Finally, we explored the impact of different parameters on the algorithm with the potential of our steganography algorithm through parameter selection experiments. We also verify the effectiveness of our validation model to select the best steganographic images. The experiments show that our algorithm can achieve a 100% information embedding rate and more than 95% steganography success rate under the set condition of 3 samples per group. In addition, our embedded information can be hardly detected by other OCR models.

Preservation and Encryption in DNA Digital Data Storage

The exponential growth of the total amount of global data presents a huge challenge to mainstream storage media. The emergence of molecular digital storage inspires the development of the new-generation higher-density digital data storage. In particular, DNA with high storage density, reproducibility, and long recoverable lifetime behaves the ideal representative of molecular digital storage media. With the development of DNA synthesis and sequencing technologies and the reduction of cost, DNA digital storage has attracted more and more attention and achieved significant breakthroughs. Herein, this Review briefly describes the workflow of DNA storage, and highlights the storage step of DNA digital data storage. Then, according to different information storage forms, the current DNA information encryption methods are emphatically expounded. Finally, the brief perspectives on the current challenges and optimizing proposals in DNA information preservation and encryption are presented.

A Novel Steganography-Based Pattern for Print Matter Anti-Counterfeiting by Smartphone Cameras

Print matter authentication based on anti-counterfeiting techniques has received continuously increasing concern from academia and industry. However, the existing printing anti-counterfeiting solutions often have the defects of poor identification experience, high cost, or weak anti-counterfeiting ability, and cannot achieve pre-sale anti-counterfeiting. Therefore, a novel steganography-based pattern for print matter anti-counterfeiting by smartphone cameras is proposed in this study. Firstly, every pixel in the original binary message image (such as QR code) is replaced by a square pixel block with the same binary gray value of 0 or 255 (the first-level expansion). Secondly, the obtained image is encrypted based on the logistic chaotic sequence, and then scrambled by Arnold transform. Lastly, once again every pixel in the generated image is replaced with a square pixel block (the second-level expansion), the size and gray value of which can be set to control the semi-fragile ability to distinguish an originally printed pattern from its illegitimate copy. If the message extracted from the printed pattern through the inverse procedure is complete enough to decode and read, the pattern is assumed to be an original print. Experimental results verify the advancement and effectiveness of the proposed scheme in distinguishing the copied pattern.

Direct Spread Spectrum Technology for Data Hiding in Audio

Direct spread spectrum technology is traditionally used in radio communication systems with multiple access, for example, in CDMA standards, in global satellite navigation systems, in Wi-Fi network wireless protocols, etc. It ensures high security and reliability of information transfer. In addition, spread spectrum technology provides the transmitted signals with a noise-like appearance, thus hiding the semantic content of the messages. We researched this technology for other implementations. The purpose of our study was to investigate new technologies for hiding data in multimedia files. In particular, we investigated the direct spread spectrum in the context of the development of methods for hiding data in audio containers. We considered various spreading sequences (chip codes) and also explored their use for hiding information in audio files. We conducted experimental studies and estimated the bit error rate (BER) in the recovered data. The article also evaluates the distortion of an audio container by the peak signal-to-noise ratio (PSNR). The results of our research enable us to find out which method of forming chip codes gives a lower BER with equal PSNR. We provide recommendations on the formation of spreading sequences to reliably and safely hide informational messages in audio files.

Embedding Information into or onto Additively Manufactured Parts: A Review of QR Codes, Steganography and Watermarking Methods

The paper gives a detailed review of the approaches adopted for embedding information into/onto additively manufactured parts. The primary purpose of this paper is to review all the techniques adopted for embedding information, highlight notable trends and improvements in these works, and provide design and manufacturing pipelines to realize most of these works. It classifies these approaches into four different categories and summarizes the works carried out in each field. It also compares all the results in textual and tabular forms and then gives a detailed conclusion of the best works in terms of application and effectiveness. The four categories discussed are 3D QR codes, 3D watermarking, steganography and nonclassified methods. Lastly, it discusses the future extensions and potential improvements in the field of embedding information, while exploring manufacturing technologies.

A Dynamic Four-Step Data Security Model for Data in Cloud Computing Based on Cryptography and Steganography

Cloud computing is a rapidly expanding field. It allows users to access computer system resources as needed, particularly data storage and computational power, without managing them directly. This paper aims to create a data security model based on cryptography and steganography for data in cloud computing that seeks to reduce existing security and privacy concerns, such as data loss, data manipulation, and data theft. To identify the problem and determine its core cause, we studied various literature on existing cloud computing security models. This study utilizes design science research methodology. The design science research approach includes problem identification, requirements elicitation, artifact design and development, demonstration, and assessment. Design thinking and the Python programming language are used to build the artifact, and discussion about its working is represented using histograms, tables, and algorithms. This paper's output is a four-step data security model based on Rivest-Shamir-Adleman, Advanced Encryption Standard, and identity-based encryption algorithms alongside Least Significant Bit steganography. The four steps are data protection and security through encryption algorithms, steganography, data backup and recovery, and data sharing. This proposed approach ensures more cloud data redundancy, flexibility, efficiency, and security by protecting data confidentiality, privacy, and integrity from attackers.

Vectorial Compound Metapixels for Arbitrary Nonorthogonal Polarization Steganography

Malus' law regulating the intensity of light when passed through a polarizer, forms the solid basis for image steganography based on orthogonal polarizations of light to convey hidden information without adverse perceptions, which underpins important practices in information encryptions, anti-counterfeitings, and security labels. Unfortunately, the restriction to orthogonal states being taken for granted in the common perceptions fails to advance cryptoinformation to upgraded levels of security. By introducing a vectorial compound metapixel design, arbitrary nonorthogonal polarization multiplexing of independent grayscale images with high fidelity and strong concealment is demonstrated. The Jones matrix treatment of compound metapixels consisting of double atoms with tailored in-plane orientation sum and difference allows point-by-point configuring of both the amplitude and polarization rotations of the output beam in an analytical and linear form. With this, both multiplexing two continuous grayscale images in arbitrary nonorthogonal polarization angles and concealing grayscale image on another in an arbitrary disclosure angle window are experimentally demonstrated in the visible TiO₂ metasurface platform. The methods shed new light on multifarious metaoptics by harnessing the new degree of freedom and unlock the full potential of metasurface polarization optics.

ThermoSteg-Covert Channel for Microbolometer Thermographic Cameras

The article presents a new concept—steganography in thermography. Steganography is a technique of hiding information in a non-obvious way and belongs to sciences related to information security. The proposed method, called ThermoSteg, uses a modification of one of the parameters of the thermal imaging camera—integration time—to embed the signal containing hidden information. Integration time changing makes the microbolometer array heat up while reading the sensors. The covert information can be extracted from the stream of thermograms recorded by another thermal camera that observes the first one. The covert channel created with the ThermoSteg method allows the transmission of covert data using a thermal sensor as a wireless data transmitter. This article describes a physical phenomenon that is exploited by the ThermoSteg method and two proposed methods of covert data extraction, and presents the results of experiments.

StegoFrameOrder-MAC Layer Covert Network Channel for Wireless IEEE 802.11 Networks

The proposed StegoFrameOrder (SFO) method enables the transmission of covert data in wireless computer networks exploiting non-deterministic algorithms of medium access (such as the distributed coordination function), especially in IEEE 802.11 networks. Such a covert channel enables the possibility of leaking crucial information outside secured network in a manner that is difficult to detect. The SFO method embeds hidden bits of information in the relative order of frames transmitted by wireless terminals operating on the same radio channel. The paper presents an idea of this covert channel, its implementation, and possible variants. The paper also discusses implementing the SFO method in a real environment and the experiments performed in the real-world scenario.

Steganographic Analysis of Blockchains

Steganography is one of the ways to hide data between parties. Its use can be worrisome, e.g., to hide illegal communications. Researchers found that public blockchains can be an attractive place to hide communications; however, there is not much evidence of actual use in blockchains. Besides, previous work showed a lack of steganalysis methods for blockchains. In this context, we present a steganalysis approach for blockchains, evaluating it in Bitcoin and Ethereum, both popular cryptocurrencies. The main objective is to answer if one can find steganography in real case scenarios, focusing on LSB of addresses and nonces. Our sequential analysis included 253 GiB and 107 GiB of bitcoin and ethereum, respectively. We also analyzed up to 98 million bitcoin clusters. We found that bitcoin clusters could carry up to 360 KiB of hidden data if used for such a purpose. We have not found any concrete evidence of hidden data in the blockchains. The sequential analysis may not capture the perspective of the users of the blockchain network. In this case, we recommend clustering analysis, but it depends on the clustering method’s accuracy. Steganalysis is an essential aspect of blockchain security.

From Constellation Dithering to NOMA Multiple Access: Security in Wireless Systems

In recent years, there has been a noticeable increase in interest in the possibilities of embedding additional data in the constellation of an already existing information signal in radio technology. This solution more precisely is based on adding a low power signal (or signals) to a stronger signal (cover). As will be described in the article, this technique is used in numerous radio communication areas, such as watermarking, covert channel creation, and multiple access techniques. Typically, those areas are considered as independent research topics. Our comparison suggests that these areas are closely related. In this article, a comprehensive survey of the implementation of signal superposition is conducted with an emphasis on the similarities and differences between individual solutions. Since the nature of the signal model entails certain problems in the security area, we provide the reader with a review of the state-of-the-art research on this topic, including the PLS (physical layer security) and LPD (low probability of detection) issues.

Eigenfaces-Based Steganography

In this paper we propose a novel transform domain steganography technique—hiding a message in components of linear combination of high order eigenfaces vectors. By high order we mean eigenvectors responsible for dimensions with low amount of overall image variance, which are usually related to high-frequency parameters of image (details). The study found that when the method was trained on large enough data sets, image quality was nearly unaffected by modification of some linear combination coefficients used as PCA-based features. The proposed method is only limited to facial images, but in the era of overwhelming influence of social media, hundreds of thousands of selfies uploaded every day to social networks do not arouse any suspicion as a potential steganography communication channel. From our best knowledge there is no description of any popular steganography method that utilizes eigenfaces image domain. Due to this fact we have performed extensive evaluation of our method using at least 200,000 facial images for training and robustness evaluation of proposed approach. The obtained results are very promising. What is more, our numerical comparison with other state-of-the-art algorithms proved that eigenfaces-based steganography is among most robust methods against compression attack. The proposed research can be reproduced because we use publicly accessible data set and our implementation can be downloaded.

Steganography and Steganalysis in Voice over IP: A Review

The rapid advance and popularization of VoIP (Voice over IP) has also brought security issues. VoIP-based secure voice communication has two sides: first, for legitimate users, the secret voice can be embedded in the carrier and transmitted safely in the channel to prevent privacy leakage and ensure data security; second, for illegal users, the use of VoIP Voice communication hides and transmits illegal information, leading to security incidents. Therefore, in recent years, steganography and steganography analysis based on VoIP have gradually become research hotspots in the field of information security. Steganography and steganalysis based on VoIP can be divided into two categories, depending on where the secret information is embedded: steganography and steganalysis based on voice payload or protocol. The former mainly regards voice payload as the carrier, and steganography or steganalysis is performed with respect to the payload. It can be subdivided into steganography and steganalysis based on FBC (fixed codebook), LPC (linear prediction coefficient), and ACB (adaptive codebook). The latter uses various protocols as the carrier and performs steganography or steganalysis with respect to some fields of the protocol header and the timing of the voice packet. It can be divided into steganography and steganalysis based on the network layer, the transport layer, and the application layer. Recent research results of steganography and steganalysis based on protocol and voice payload are classified in this paper, and the paper also summarizes their characteristics, advantages, and disadvantages. The development direction of future research is analyzed. Therefore, this research can provide good help and guidance for researchers in related fields.

Bio-signal data sharing security through watermarking: a technical survey

Due to smart healthcare systems highly connected information and communications technologies, sensitive medical information and records are easily transmitted over the networks. However, stealing of healthcare data is increasing crime every day to greatly impact on financial loss. In order to this, researchers are developing various cost-effective bio-signal based data hiding techniques for smart healthcare applications. In this paper, we first introduce various aspects of data hiding along with major properties, generic embedding and extraction process, and recent applications. This survey provides a comprehensive survey on data hiding techniques, and their new trends for solving new challenges in real-world applications. Then, we survey the various notable bio-signal based data hiding techniques. The summary of some notable techniques in terms of their objective, type of data hiding, methodology and database used, performance metrics, important features, and limitations are also presented in tabular form. At the end, we discuss the major issues and research directions to explore the promising areas for future research.

Protecting Physical Communications in 5G C-RAN Architectures through Resonant Mechanisms in Optical Media

Future 5G networks are characterized by three basic ideas: enhanced mobile broadband communications, massive machine-type communications, and ultra-low-latency communications. Any of these requirements needs, to be fulfilled, the implementation of high-efficiency technologies at all levels. This includes some of the costliest mechanisms in terms of computational time and bitrate: information protection solutions. Typical techniques in this area employ complex algorithms and large protocol headers, which strongly reduces the effective baud rate and latency of future 5G networks and communications. This is especially relevant in the access network, which in 5G networks will follow a cloud-based architecture, where thousands of different devices must communicate, before aggregating all those streams to be sent to the backbone. Then, new and more efficient mechanisms are needed in the cloud radio access networks (C-RAN) for future 5G systems. Therefore, in this paper it is proposed a novel information protection scheme for C-RAN architectures based on resonant phenomena in optical fibers communicating the fronthaul and backhaul in 5G networks. Resonant structures and physical nonlinearities generate a chaotic signal which may encrypt and hide at physical level every communication stream in a very efficient manner. To evaluate the proposed mechanism, an experimental validation based on simulation techniques is also described and results discussed.

A Robust Quasi-Quantum Walks-Based Steganography Protocol for Secure Transmission of Images on Cloud-Based E-healthcare Platforms

Traditionally, tamper-proof steganography involves using efficient protocols to encrypt the stego cover image and/or hidden message prior to embedding it into the carrier object. However, as the inevitable transition to the quantum computing paradigm beckons, its immense computing power will be exploited to violate even the best non-quantum, i.e., classical, stego protocol. On its part, quantum walks can be tailored to utilise their astounding 'quantumness' to propagate nonlinear chaotic behaviours as well as its sufficient sensitivity to alterations in primary key parameters both important properties for efficient information security. Our study explores using a classical (i.e., quantum-inspired) rendition of the controlled alternate quantum walks (i.e., CAQWs) model to fabricate a robust image steganography protocol for cloud-based E-healthcare platforms by locating content that overlays the secret (or hidden) bits. The design employed in our technique precludes the need for pre and/or post encryption of the carrier and secret images. Furthermore, our design simplifies the process to extract the confidential (hidden) information since only the stego image and primary states to run the CAQWs are required. We validate our proposed protocol on a dataset of medical images, which exhibited remarkable outcomes in terms of their security, good visual quality, high resistance to data loss attacks, high embedding capacity, etc., making the proposed scheme a veritable strategy for efficient medical image steganography.

Distributed Steganography in PDF Files-Secrets Hidden in Modified Pages

This paper shows how to diffuse a message and hide it in multiple PDF files. Presented method uses dereferenced objects and secret splitting or sharing algorithms. It is applicable to various types of PDF files, including text documents, presentations, scanned images etc. Because hiding process is based on structure manipulation, the solution may be easily combined with content-dependent steganographic techniques. The hidden pages are not visible in typical application usage, which was tested with seven different programs.

Improved ECG Watermarking Technique Using Curvelet Transform

Hiding data in electrocardiogram signals are a big challenge due to the embedded information that can hamper the accuracy of disease detection. On the other hand, hiding data into ECG signals provides more security for, and authenticity of, the patient’s data. Some recent studies used non-blind watermarking techniques to embed patient information and data of a patient into ECG signals. However, these techniques are not robust against attacks with noise and show a low performance in terms of parameters such as peak signal to noise ratio (PSNR), normalized correlation (NC), mean square error (MSE), percentage residual difference (PRD), bit error rate (BER), structure similarity index measure (SSIM). In this study, an improved blind ECG-watermarking technique is proposed to embed the information of the patient’s data into the ECG signals using curvelet transform. The Euclidean distance between every two curvelet coefficients was computed to cluster the curvelet coefficients and after this, data were embedded into the selected clusters. This was an improvement not only in terms of extracting a hidden message from the watermarked ECG signals, but also robust against image-processing attacks. Performance metrics of SSIM, NC, PSNR and BER were used to measure the superiority of presented work. KL divergence and PRD were also used to reveal data hiding in curvelet coefficients of ECG without disturbing the original signal. The simulation results also demonstrated that the clustering method in the curvelet domain provided the best performance—even when the hidden messages were large size.

Information Coding in a Reconfigurable DNA Origami Domino Array

DNA nanostructures with programmable nanoscale patterns has been achieved in the past decades, and molecular information coding (MIC) on those designed nanostructures has gained increasing attention for information security. However, achieving steganography and cryptography synchronously on DNA nanostructures remains a challenge. Herein, we demonstrated MIC in a reconfigurable DNA origami domino array (DODA), which can reconfigure intrinsic patterns but keep the DODA outline the same for steganography. When a set of keys (DNA strands) are added, the cryptographic data can be translated into visible patterns within DODA. More complex cryptography with the ASCII code within a programmable 6×6 lattice is demonstrated to demosntrate the versatility of MIC in the DODA. Furthermore, an anti-counterfeiting approach based on conformational transformation-mediated toehold strand displacement reaction is designed to protect MIC from decoding and falsification.

BOOST: Medical Image Steganography Using Nuclear Spin Generator

In this study, we present a medical image stego hiding scheme using a nuclear spin generator system. Detailed theoretical and experimental analysis is provided on the proposed algorithm using histogram analysis, peak signal-to-noise ratio, key space calculation, and statistical package analysis. The provided results show good performance of the brand new medical image steganographic scheme.

Graphene-Based Steganographic Aptasensor for Information Computing and Monitoring Toxins of Biofilm in Food

Fungi-forming biofilm would produce various toxins in food. The toxin contamination will cause great harm to food and human health. Herein, a novel graphene-based steganographic aptasensor was assembled for multifunctional applications, which depended on the specific recognition and information encoding ability of DNA aptamers [mycotoxins, including zearalenone (ZEN) and ochratoxin A (OTA) aptamers, as models] and the selective absorption and fluorescence quenching capacities of graphene oxide (GO). The graphene-based steganographic aptasensor can be regarded as an information encryption and steganographic system using GO as a cover, aptamers for specific target recognition as information carriers and dual targets (ZEN and OTA) as special keys. In our work, the fluorescence of capture probes (Cy3 aptamer and Alexa Fluor 488 aptamer) was quenched by GO to realize information encryption. In the presence of dual targets in the GO-APT solution, Cy3 aptamer (APT1), and Alexa Fluor 488 aptamer (APT2) were released from the surface of GO, decrypting the hidden information. In addition, our work offers a sensor for rapid and sensitive simultaneous fluorescence determination of ZEN and OTA. The detection limit of the aptasensor was 1.797 ng/ml for ZEN and 1.484 ng/ml for OTA. In addition, the graphene-based steganographic aptasensor can be used to construct a molecular logic gate system in which GO, aptamers, and mycotoxins are employed as the input and compounds and fluorescence signals were used as the output. This would be helpful to control the biofilm toxin in the future.

High-Payload Data-Hiding Method for AMBTC Decompressed Images

Data hiding is the art of embedding data into a cover image without any perceptual distortion of the cover image. Moreover, data hiding is a very crucial research topic in information security because it can be used for various applications. In this study, we proposed a high-capacity data-hiding scheme for absolute moment block truncation coding (AMBTC) decompressed images. We statistically analyzed the composition of the secret data string and developed a unique encoding and decoding dictionary search for adjusting pixel values. The dictionary was used in the embedding and extraction stages. The dictionary provides high data-hiding capacity because the secret data was compressed using dictionary-based coding. The experimental results of this study reveal that the proposed scheme is better than the existing schemes, with respect to the data-hiding capacity and visual quality.

Comparative Study of Three Steganographic Methods Using a Chaotic System and Their Universal Steganalysis Based on Three Feature Vectors

In this paper, we firstly study the security enhancement of three steganographic methods by using a proposed chaotic system. The first method, namely the Enhanced Edge Adaptive Image Steganography Based on LSB Matching Revisited (EEALSBMR), is present in the spatial domain. The two other methods, the Enhanced Discrete Cosine Transform (EDCT) and Enhanced Discrete Wavelet transform (EDWT), are present in the frequency domain. The chaotic system is extremely robust and consists of a strong chaotic generator and a 2-D Cat map. Its main role is to secure the content of a message in case a message is detected. Secondly, three blind steganalysis methods, based on multi-resolution wavelet decomposition, are used to detect whether an embedded message is hidden in the tested image (stego image) or not (cover image). The steganalysis approach is based on the hypothesis that message-embedding schemes leave statistical evidence or structure in images that can be exploited for detection. The simulation results show that the Support Vector Machine (SVM) classifier and the Fisher Linear Discriminant (FLD) cannot distinguish between cover and stego images if the message size is smaller than 20% in the EEALSBMR steganographic method and if the message size is smaller than 15% in the EDCT steganographic method. However, SVM and FLD can distinguish between cover and stego images with reasonable accuracy in the EDWT steganographic method, irrespective of the message size.

A Cancelable Iris- and Steganography-Based User Authentication System for the Internet of Things

Remote user authentication for Internet of Things (IoT) devices is critical to IoT security, as it helps prevent unauthorized access to IoT networks. Biometrics is an appealing authentication technique due to its advantages over traditional password-based authentication. However, the protection of biometric data itself is also important, as original biometric data cannot be replaced or reissued if compromised. In this paper, we propose a cancelable iris- and steganography-based user authentication system to provide user authentication and secure the original iris data. Most of the existing cancelable iris biometric systems need a user-specific key to guide feature transformation, e.g., permutation or random projection, which is also known as key-dependent transformation. One issue associated with key-dependent transformations is that if the user-specific key is compromised, some useful information can be leaked and exploited by adversaries to restore the original iris feature data. To mitigate this risk, the proposed scheme enhances system security by integrating an effective information-hiding technique-steganography. By concealing the user-specific key, the threat of key exposure-related attacks, e.g., attacks via record multiplicity, can be defused, thus heightening the overall system security and complementing the protection offered by cancelable biometric techniques.

Locating secret messages based on quantitative steganalysis

Steganography poses a serious challenge to forensics because investigators cannot identify even traces of secret messages embedded using a steganographer. Contrarily, the objective of locating steganalysis is to locate the embedded message, which should help extract the secret message. In this paper, a methodology of locating steganalysis using quantitative steganalysis is presented for multiple stego images with embedded messages along the same embedding path. Three typical quantitative steganalysis methods are applied to the methodology to locate the messages embedded using LSB re-placement. Experimental results show that the presented methods can reliably estimate the embedding positions, which verifies the validity of the presented methodology. The presented methodology points out a new use of quantitative steganalysis, and further demonstrates that it is necessary to design more precise quantitative steganalysis methods.

Information hiding based on Augmented Reality

Information hiding aims to achieve secret communication via certain carrier. However, these carrier-based methods often have different kinds of deficiencies. In order to solve the problems addressed by the traditional information hiding methods such as the difficult balance between secret embedding rate and detection rate, this paper proposes a novel approach which utilizes Augmented Reality (AR) to achieve secret communication. In this paper, we present an AR based information hiding architecture which combines information hiding, augmented reality, and deep learning methods altogether. The proposed architecture basically follows the idea of secret-key matching policy. The secret sender first maps the secret message to objects, images or coordinates, etc. The mapped objects, images or coordinates then serve as the secret key for further secret revealing. The secret key and concealing model are shared between two communication parties instead of direct transmitting the secret messages. Different secret keys can be combined in order to generate more mapping sequences. Also, deep learning based models are integrated in the architecture to extend the mapping varieties. By taking advantage of the augmented reality technique, the secret messages can be transmitted in various formats which results in higher secret embedding rate in potential. Furthermore, the proposed architecture can be seen as a useful application of coverless information hiding scheme. The experimental system realizes the proposed architecture by implementing convolutional neural network (CNN) based real-time object detection, image recognition, augmented reality and secret-key matching altogether which shows great promise in practice.

Graphene-Based Steganographically Aptasensing System for Information Computing, Encryption and Hiding, Fluorescence Sensing and in Vivo Imaging of Fish Pathogens

Inspired by information processing and communication of life based on complex molecular interactions, some artificial (bio)chemical systems have been developed for applications in molecular information processing or chemo/biosensing and imaging. However, little attention has been paid to simultaneously and comprehensively utilize the information computing, encoding, and molecular recognition capabilities of molecular-level systems (such as DNA-based systems) for multifunctional applications. Herein, a graphene-based steganographically aptasensing system was constructed for multifunctional application, which relies on specific molecular recognition and information encoding abilities of DNA aptamers ( Aeromonas hydrophila and Edwardsiella tarda-binding aptamers as models) and the selective adsorption and fluorescence quenching capacities of graphene oxide (GO). Although graphene-DNA systems have been widely used in biosensors and diagnostics, our proposed graphene-based aptasensing system can not only be utilized for fluorescence sensing and in vivo imaging of fish pathogens ( A. hydrophila and E. tarda), but can also function as a molecular-level logic computing system where the combination of matters (specific molecules or materials) as inputs produces the resulting product (matter level) or fluorescence (energy level) changes as two outputs. More importantly and interestingly, our graphene-based steganographically aptasensing system can also serve as a generally doubly cryptographic and steganographic system for sending different secret messages by using pathogen-binding DNA aptamers as information carriers, GO as a cover, and a pair of keys, that is, target pathogen as a public key, the encryption key used to encode or decode a message in DNA as a private key. Our study not only provides a novel nanobiosensing assay for rapid and effective sensing and in vivo imaging of fish pathogens, but also demonstrates a prototype of (bio)molecular steganography as an important and interesting extension direction of molecular information technology, which is helpful in probably promoting the development of multifunctional molecular-level devices or machines.

Laser-Splashed Three-Dimensional Plasmonic Nanovolcanoes for Steganography in Angular Anisotropy

Planar optics constructed from subwavelength artificial atoms have been suggested as a route to the physical realization of steganography with controlled intrinsic redundancy at single-pixel levels. Unfortunately, two-dimensional geometries with uniform flat profiles offer limited structural redundancy and make it difficult to create advanced crypto-information in multiplexed physical divisions. Here, we reveal that splashing three-dimensional (3D) plasmonic nanovolcanoes could allow for a steganographic strategy in angular anisotropy, with high resolution, full coloration, and transient control of structural profiles. Highly reproducible 3D morphologies of volcanic nanosplashes are demonstrated by creating a standardized recipe of laser parameters. Such single nanovolcanoes can be well controlled individually at different splashing stages and thus provide a lithography-free fashion to access various spectral responses of angularly coordinated transverse and vertical modes, leading to the full-range coloration. This chip-scale demonstration of steganographic color images in angular anisotropy unfolds a long-ignored scheme for structured metasurfaces and thereby provides a paradigm for information security and anticounterfeiting.

A Lightweight Protocol for Secure Video Streaming

The Internet of Things (IoT) introduces many new challenges which cannot be solved using traditional cloud and host computing models. A new architecture known as fog computing is emerging to address these technological and security gaps. Traditional security paradigms focused on providing perimeter-based protections and client/server point to point protocols (e.g., Transport Layer Security (TLS)) are no longer the best choices for addressing new security challenges in fog computing end devices, where energy and computational resources are limited. In this paper, we present a lightweight secure streaming protocol for the fog computing "Fog Node-End Device" layer. This protocol is lightweight, connectionless, supports broadcast and multicast operations, and is able to provide data source authentication, data integrity, and confidentiality. The protocol is based on simple and energy efficient cryptographic methods, such as Hash Message Authentication Codes (HMAC) and symmetrical ciphers, and uses modified User Datagram Protocol (UDP) packets to embed authentication data into streaming data. Data redundancy could be added to improve reliability in lossy networks. The experimental results summarized in this paper confirm that the proposed method efficiently uses energy and computational resources and at the same time provides security properties on par with the Datagram TLS (DTLS) standard.

Entropy-Based Video Steganalysis of Motion Vectors

In this paper, a new method is proposed for motion vector steganalysis using the entropy value and its combination with the features of the optimized motion vector. In this method, the entropy of blocks is calculated to determine their texture and the precision of their motion vectors. Then, by using a fuzzy cluster, the blocks are clustered into the blocks with high and low texture, while the membership function of each block to a high texture class indicates the texture of that block. These membership functions are used to weight the effective features that are extracted by reconstructing the motion estimation equations. Characteristics of the results indicate that the use of entropy and the irregularity of each block increases the precision of the final video classification into cover and stego classes.

An RGB colour image steganography scheme using overlapping block-based pixel-value differencing

This paper presents a steganographic scheme based on the RGB colour cover image. The secret message bits are embedded into each colour pixel sequentially by the pixel-value differencing (PVD) technique. PVD basically works on two consecutive non-overlapping components; as a result, the straightforward conventional PVD technique is not applicable to embed the secret message bits into a colour pixel, since a colour pixel consists of three colour components, i.e. red, green and blue. Hence, in the proposed scheme, initially the three colour components are represented into two overlapping blocks like the combination of red and green colour components, while another one is the combination of green and blue colour components, respectively. Later, the PVD technique is employed on each block independently to embed the secret data. The two overlapping blocks are readjusted to attain the modified three colour components. The notion of overlapping blocks has improved the embedding capacity of the cover image. The scheme has been tested on a set of colour images and satisfactory results have been achieved in terms of embedding capacity and upholding the acceptable visual quality of the stego-image.

Facilitating and securing offline e-medicine service through image steganography

E-medicine is a process to provide health care services to people using the Internet or any networking technology. In this Letter, a new idea is proposed to model the physical structure of the e-medicine system to better provide offline health care services. Smart cards are used to authenticate the user singly. A very unique technique is also suggested to verify the card owner's identity and to embed secret data to the card while providing patients' reports either at booths or at the e-medicine server system. The simulation results of card authentication and embedding procedure justify the proposed implementation.

Run-length encoding graphic rules, biochemically editable designs and steganographical numeric data embedment for DNA-based cryptographical coding system

There have been a wide variety of approaches for handling the pieces of DNA as the "unplugged" tools for digital information storage and processing, including a series of studies applied to the security-related area, such as DNA-based digital barcodes, water marks and cryptography. In the present article, novel designs of artificial genes as the media for storing the digitally compressed data for images are proposed for bio-computing purpose while natural genes principally encode for proteins. Furthermore, the proposed system allows cryptographical application of DNA through biochemically editable designs with capacity for steganographical numeric data embedment. As a model case of image-coding DNA technique application, numerically and biochemically combined protocols are employed for ciphering the given "passwords" and/or secret numbers using DNA sequences. The "passwords" of interest were decomposed into single letters and translated into the font image coded on the separate DNA chains with both the coding regions in which the images are encoded based on the novel run-length encoding rule, and the non-coding regions designed for biochemical editing and the remodeling processes revealing the hidden orientation of letters composing the original "passwords." The latter processes require the molecular biological tools for digestion and ligation of the fragmented DNA molecules targeting at the polymerase chain reaction-engineered termini of the chains. Lastly, additional protocols for steganographical overwriting of the numeric data of interests over the image-coding DNA are also discussed.