Hidden Bits Research Articles

Hiding scrambled text messages in speech signals using a lightweight hyperchaotic map and conditional LSB mechanism.

This study presents a lightweight, secure audio steganography system for hiding text messages for transmission over the Internet, with the aim of addressing the current problems of high computational cost and insufficient security identified in earlier studies. We propose a two-phase functioning mechanism. Text characters are first transformed into ASCII code and stored in a vector, which is then divided into three sub-vectors. These sub-vectors are scrambled using two low-complexity operations, namely a forward-backward reading technique and an odd-even index. Two scrambling loops are performed, the first on the small sub-vectors the second on the vector as a whole. In the hiding phase, the speech signal samples are divided into 256 blocks using only 200 values per block, and low-complexity quadratic and the Hénon maps are used to hide the speech signal in a random manner. The conditional LSB is applied as a low-complexity algorithm to identify hidden bits, and a special hyperchaotic map algorithm is developed to randomly choose locations. The proposed approach provides good security for a scrambled text message, with high SNR and PSNR, small MSE and PESQ, a SSIM value of close to one (As indicated in Tables 1, 2, 3, and 4), a BER value of close to zero (as shown in table 8), NCC value near +1 (as shown in table 8), and an MOS value of near five (as described in table 6), as well as a low computational hiding cost.

Multi-objective based unbiased community identification in dynamic social networks

A network is a topological arrangement of its two basic elements, nodes and edges. Networks in the real world are not static. They tend to evolve with time, causing the set of nodes and edges to alter as well. They consist of several hidden bits of data whose analysis have drawn significant research interest. Identifying groups of similar nodes or edges helps in gaining knowledge about their interaction patterns. These groups are known as communities, which can be disjoint or overlapping. The dynamic nature of the network also impact its current community structure and makes it difficult to keep track of them. The paper presents a multi-objective optimization approach for identifying community structure in a dynamic network. A network is considered as a series of events generated over time, where each event is a new edge introduced at a time. The proposed algorithm uses three objective functions that are inspired from network properties. The community of a node corresponding to an input edge is updated by an algorithm based on its newness. The algorithm uses the Pareto front principle to identify the optimal community. The algorithm is evaluated over 12 datasets and compared to 10 state-of-the-art algorithms. It shows superior performance on real and connected datasets and also performs well for disconnected datasets. The algorithm is evaluated using both accuracy and quality metrics, with the quality metrics slightly outweighing the accuracy metrics.

A Secure and High Capacity Image Steganography Approach Using Huffman Coding and RSA Encryption

Steganography is the practice of hiding data, such as images, videos, or text, within a cover image without it being detectable by the human eye. Several factors, such as the capacity, security, and robustness of the technique, are essential when transferring information using this method. In this study, we propose a new approach to image steganography that improves the Least Significant Bit (LSB) technique by utilizing images of 24 bits in each pixel. Improving the capacity and security of LSB-based steganography requires a combination of techniques, such as indirect embedding, embedding in multiple channels, and applying cryptographic and compression techniques. This approach conducts by encrypting each compressed secret message bit with the most significant bit of the red channel and then saving the output bit (hidden bit) in the least significant bit of the (green/blue) channel according to the row value (odd/ even). To further security, the suggested approach uses multi-level encryption; employs RSA to encrypt the secret message before applying the Huffman compression and encrypting the hidden bit by (XOR/XNOR) in the embedding method based on the row value of the pixel. Meanwhile, it is planned to use the Huffman coding technique to shorten the length of the encrypted message that will be inserted in the cover image. For the color photos in this work, the standard images were acquired from a standard dataset (USC-SIPI). The suggested approach performs better when measured in terms of mean square error (MSE), peak signal-to-noise ratio (PSNR), and comparison to findings from related prior efforts.

The Design and Implementation of a Steganographic Communication System over In-Band Acoustical Channels

This article presents SoundSticker, a system for steganographic, in-band data communication over an acoustic channel. In contrast with recent works that hide bits in inaudible frequency bands, SoundSticker embeds hidden bits in the audible sounds, making them more reliably survive audio codecs and bandpass filtering, while achieving a higher data rate and remaining imperceptible to a listener. The key observation behind SoundSticker is that the human ear is less sensitive to the audio phase changes than the frequency and amplitude changes, which leaves us an opportunity to alter the phase of an audio clip to convey hidden information. We take advantage of this opportunity and build an OFDM-based physical layer. To make this PHY-layer design work for a variety of end devices with heterogeneous computation resources, SoundSticker addresses multiple technical challenges including perceivable waveform artifacts caused by the phase-based modulation, bit rate adaptation without channel sounding and real-time preamble detection. Our prototype on both smartphones and ESP32 platforms demonstrates SoundSticker’s superior performance against the state of the arts, while preserving excellent sound quality and remaining unaffected by common audio codecs like MP3 and AAC. Audio clips produced by SoundSticker can be found at https://soundsticker.github.io/ .

Novel Hidden Bit Location Method towards JPEG Steganography

Image steganalysis has been widely studied, most of which can only complete the binary task of identifying the existence of hidden bits in an inquiry image. Currently, although some algorithms have been proposed to locate hidden bits, most of them mainly focus on the spatial domain, while usually ignoring the study of locating secret bits hidden in DCT domain for JPEG image. To address that challengeable problem, in this paper, towards two classical steganographic algorithms JSteg and F5, hiding bits in DCT domain, we propose a novel payload location method. The principal step of payload location is to estimate the cover image. We novelly propose to assign the different weights to the DCT coefficient residual in virtue of the texture of regions measured by the local variance, leading to the remarkable improvement of location results. Compared with the state of the art, the numerical experiments empirically verify that our proposed location method achieves the superior performance. In particular, when locating hidden bits in JSteg steganographic images with quality factor of 95 at the payload 0.1, the accuracy of location is remarkably improved from 46.18% to 90.22%.

Toward Steganographic Payload Location via Neighboring Weight Algorithm

Modern steganalysis has been widely investigated, most of which mainly focus on dealing with the problem of detecting whether an inquiry image contains hidden information. However, few articles in the literature study the location of secret bits hidden by modern adaptive steganography. In this paper, we propose a novel algorithm for locating steganographic payload in the spatial domain. We first predict the steganographic scheme and its payload, which is used for generating a random bitstream. Then, the random bits are embedded in the stego image based on the cost matrix in the framework of Syndrome-Trellis Codes (STCs). Next, relying on the differences between two stego images, the extended modification map in couple with the neighboring weight algorithm can be acquired, leading to the location of the hidden bits. Compared with the prior art, the extensive experiments verify that our proposed locating algorithm performs better, in terms of locating accuracy and efficiency.

Robust Reversible Audio Watermarking Scheme for Telemedicine and Privacy Protection

The leakage of medical audio data in telemedicine seriously violates the privacy of patients. In order to avoid the leakage of patient information in telemedicine, a two-stage reversible robust audio watermarking algorithm is proposed to protect medical audio data. The scheme decomposes the medical audio into two independent embedding domains, embeds the robust watermark and the reversible watermark into the two domains respectively. In order to ensure the audio quality, the Hurst exponent is used to find a suitable position for watermark embedding. Due to the independence of the two embedding domains, the embedding of the second-stage reversible watermark will not affect the first-stage watermark, so the robustness of the first-stage watermark can be well maintained. In the second stage, the correlation between the sampling points in the medical audio is used to modify the hidden bits of the histogram to reduce the modification of the medical audio and reduce the distortion caused by reversible embedding. Simulation experiments show that this scheme has strong robustness against signal processing operations such as MP3 compression of 48 db, additive white Gaussian noise (AWGN) of 20 db, low-pass filtering, resampling, re-quantization and other attacks, and has good imperceptibility.

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.

Robust and reversible image watermarking in homomorphic encrypted domain

This paper proposes a robust and reversible watermarking scheme for the encrypted image by using Paillier cryptosystem. In the proposed method, the original image is divided into a number of non-overlapping blocks sized by 8 × 8 and Paillier cryptosystem is applied to encrypt the pixels in each block. Firstly, a data hider can calculate the statistical values of encrypted blocks by employing modular multiplicative inverse (MMI) method and looking for a mapping table. Then a watermark sequence can be embedded into the encrypted image by shifting the histogram of the statistical values. On the receiver side, the shifted histogram can be obtained from both the encrypted image and the decrypted image. Furthermore, the embedded watermark can be extracted from the shifted histogram. The encrypted original image can be restored by employing inverse operations of histogram shifting. This is followed by a decryption operation to restore the original image. In the proposed method, the hidden bits can still be extracted correctly under some typical content-preserving operations, such as JPEG/JPEG2000 compression and additive Gaussian noise. Compared with the previous reversible watermarking methods in plaintext domain, the proposed method has satisfactory performance in image quality and robustness. Experimental results have shown the validity of the proposed method.

Secure image hiding in speech signal by steganography-mining and encryption

<span>Information hiding techniques are constantly evolving due to the increased need for security and confidentiality. This paper proposes a working mechanism in three phases. The first phase includes scrambling the values of the gray image depending on a series of keys that are generated using a quantum chaotic map. The second phase generates hybrid keys by mixing a Zaslavsky and a 3D Hanon map that are used to encrypt the gray image values produced after the scramble. Finally, in the third phase, a new algorithm is suggested to hide the encrypted gray image at random locations within a speech file. This algorithm includes the LSB algorithm to determine the hidden bits and the zero-crossing K-means algorithm in selecting locations mining in a scattered manner so that hackers cannot easily retrieve the hidden data of any hacked person. Also used a fractional fourier transform to choose magnitude value as specific data to hide encoded image data. The measures MSE, PSNR, NSCR, and UACI are using to measure the work efficiency in the encryption algorithm, and in measuring the efficiency of the hidden algorithm, use the measures SNR, PSNR, and MSE. The results of the paper are encouraging and efficient compared to other algorithms that performed the same work. Hence our results show the larger the image dimensions used, the better the values.</span>

Method for Protection of Copyright on Vector Data

The paper proposes a method of copyright protection for vector maps, based on the embedding of raster digital watermarks. The method combines original ideas, namely, a vector data watermarking approach that does not distort the coordinate information of vector objects and embedding of noise-like images that encode a binary sequence. The use of noise-like carrier allows to simplify the verification procedure, and also to ensure the resistance of the hidden bit sequence to distortions, including interpolation errors. In comparison with previous investigations made by the authors when solving problems of vector data protection, the robustness of the embedded noise-like digital watermarks has been significantly increased by developing a new algorithm for detection of the binary sequence hidden in the spectrum of a noise-like image. The purpose of the experimental studies was to assess the attainable probability of correct sequence extraction for various parameters and embedding conditions. The study of information capacity showed that the potential amount of information embedded in each polygon without distorting the watermark sequence depends on the type of a map, namely on the number of vertices that make up each polygon. An experimental study on robustness against potentially possible transformations aimed at maliciously deleting the digital watermark from the vector map is performed. The developed method demonstrates resistance to affine transformations, cropping, addition, removal and reordering of vertices / objects, and, thus, seems to be the optimal solution to the problem of copyright protection for vector data. The analysis of the method quality according to the criteria of accuracy, durability, information capacity, and computational complexity is performed. The results of all conducted studies confirm the efficiency and the effectiveness of the proposed method for vector map protection, as well as its distinct advantage over the prior art.

CPA-Secure Privacy-Preserving Reversible Data Hiding for JPEG Images

The Encrypted Image Reversible Data Hiding (EIRDH) is a hot area of research in multimedia outsourcing scenarios. In such a setting, a content owner possesses confidential images that he wants to upload to an untrusted server. The server is supposed to embed a secret message in the images before sending them to potential receivers, and the receivers expect to recover the original images without any distortion. EIRDH schemes are designed to meet reversible data hiding goals while preserving the confidentiality of the host images. Confidentiality is provided by means of encryption algorithms; however, these algorithms, in turn, introduce the challenge of dealing with ciphered images in both embedding and extraction phases. The current paper tries to propose a privacy-preserving reversible data hiding scheme for JPEG images without the need for any levels of decompression. We propose an elliptic curve-based asymmetric, commutative, and separable EIRDH method, in which no entities other than the sender and the eligible receiver of the hidden message (embedded in the encrypted image) are able to recognize its existence. In particular, even the server that performs the embedding remains completely unaware of the content of the images. An important security feature of our scheme involves the security of its multiple encryptions against Chosen-Plaintext Attack (CPA), which is an attack model that assumes the adversary can obtain the encryptions of the images on his choice to achieve possible extra information to attack. Experimental results show that our scheme achieves full reversibility and a satisfactory level of capacity, while it accurately extracts all the hidden bits.

An efficient reversible ECG steganography by adaptive LSB approach based on 1D FDCT domain

Based on the processing of one-dimensional fast discrete cosine transform (1D FDCT) coefficients, we present an efficient reversible data hiding method for electrocardiogram (ECG) signal. The proposed method is implemented in two phases. The purpose of phase-I is to classify the FDCT (host) bundles, where each input bundle will be attributed to one of four different bundles. The aim of phase-II is to embed data bits in the selected coefficients of the classified bundles according to a predetermined bit-index table (which generated from phase-I) via adaptive least significant bit (LSB) technique. Simulations confirmed that hidden bits were extracted without distortion and the original ECG signal can be completely recovered. Furthermore, a good perceived quality and a hiding capacity superior to existing techniques were achieved. Moreover, our method is robust against attacks such as noise addition, inversion, truncation, translations, and so on. Notice that the robustness is rarely seen in conventional reversible ECG steganography methods. Since this method has a fast computation speed, it is feasible for real-time applications and can be installed in the health care devices such as the wearable ECG measure equipment.

Quantum-classical reinforcement learning for decoding noisy classical parity information

Learning a hidden parity function from noisy data, known as learning parity with noise (LPN), is an example of intelligent behavior that aims to generalize a concept based on noisy examples. The solution to LPN immediately leads to decoding a random binary linear code in the presence of classification noise. This problem is thought to be intractable classically, but can be solved efficiently if a quantum oracle can be queried. However, in practice, a learner is likely to obtain classical data. In this work, we show that a naive application of the quantum LPN algorithm to classical data encoded in an equal superposition state requires an exponential sample complexity. We then propose a quantum-classical reinforcement learning algorithm to solve the LPN problem for classical data and demonstrate a significant reduction in the sample complexity compared with the naive approach. Simulations with a hidden bit string of length up to 12 show that the quantum-classical reinforcement learning performs better than known classical algorithms when the sample complexity, run time, and robustness to classical noise are collectively considered. Our algorithm is robust to any noise in the quantum circuit that effectively appears as Pauli errors on the final state.

ACO Based Variable Least Significant Bits Data Hiding in Edges Using IDIBS Algorithm

This work presents a double asymmetric data hiding technique. The first asymmetry is created by hiding secret data in the complex region of the cover image and keep the smooth region unaffected. Then another asymmetry is developed by hiding a different number of secret bits in the various pixels of the complex region. The proposed technique uses the ant colony optimization (ACO) based technique for the classification of complex and smooth region pixels. Then, the variable least significant bits (VLSB) data hiding framework is used to hide secret bits in the complex region of the cover image. A distance-based substitution technique, namely increasing distance increasing bits substitution algorithm, is used to ensure the asymmetry in the number of hidden bits. The double asymmetric framework enhances the security of the hidden secret data and makes the retrieval of hidden information difficult for unauthorized users. The algorithm results in high-quality stego images, and the hidden information does not attract the human visual system (HVS).

Simple, robust and secure data hiding based on CRT feature extraction and closed-loop chaotic encryption system

Robust data hiding methods are basically used when rightful ownership is intended and/or transmitting channel is prone to noise. In this paper, a robust and secure data hiding method is proposed in Tchebichef domain. For feature extraction, remainders of Tchebichef coefficients are calculated according to Chinese remainder theorem (CRT). Distances of these remainders are utilized as the extracted features. These distances are then modified according to the hidden bits, to complete the embedding process. To reduce the chance of illegal access and increase the security of the proposed method, a closed-loop chaotic encryption system (CLCES) has been introduced. The proposed CLCES requires very little side information and produces extremely sensitive noise-like sequences with high security. Robustness and security of the proposed method have been analyzed. Comparison results with other related methods in the current literature confirm the superiority of the proposed method. Due to its simplicity, the proposed method is a good candidate for real-time data hiding applications.

LSB based steganography with OCR: an intelligent amalgamation

Steganography, the art of hiding information within information, has an added advantage over cryptography as the person viewing the object in which the information is hidden has no knowledge of the presence of any hidden information. The Least Significant Bit (LSB) embedding technique which is one of the widely used techniques ensures an indiscernible change in the cover image oblivious to the human eye. In this paper, an Optical Character Recognition (OCR) based Steganographic technique is introduced, in which message, in its feature form, is embedded in the cover image. We extract character level features from images which contain the textual message, and embed these features in the cover image, strengthening the data hiding objective of steganography. This is because an intruder has to know about the presence of features as hidden bits and even thereafter has to have trained OCR model to retrieve the texts from the decoded information i.e. from the features. We validate our results on an English Printed Character dataset (Chars74K Dataset), and present the evaluation results for varied LSBs.

Adaptive Speech Information Hiding Method Based on K-Means

In secure communication, finding bits that used for steganography is essential for effective and high-quality speech information hiding. This paper presents an adaptive speech information hiding method based on K-means, which can quickly find hidden bits. This method uses K-means algorithm to detect effective hidden bits through clustering and embeds secret information with different matrices to achieve good efficiency utilization of hidden bits. This proposed method embeds secret information according to the clustering result and the matrix coding at the transmitting end and extracts the secret information according to the corresponding embedding matrix ate the receiving end. Thereby implementing secure communication over VoIP. The experimental results indicate that the proposed method has better speech quality (PESQ is reduced by about 1.5%) while achieving a higher embedding capacity (up to 976 bit/s), and it shows strong concealment.

High-Capacity Reversible Data Hiding in Encrypted Images by Bit Plane Partition and MSB Prediction

This paper proposes a high-capacity scheme for reversible data hiding (RDH) in encrypted images. The proposed scheme is based on a new preprocessing method by bit plane partition. Specifically, the values in the less significant bit planes are reversibly hidden into the other bit planes. Consequently, the room in the less significant bit planes can be vacated to generate a preprocessed image, from which the original image can be recovered by extracting the hidden bit values and writing them back. After encrypting the preprocessed image with a stream cipher, the vacated room can be used to accommodate extra data, which can be retrieved without image decryption. In addition, the embedding capacity can be further increased by adopting an efficient most significant bit (MSB) prediction method before image encryption. Compared with the state-of-the-art RDH schemes for encrypted images, the experimental results show that higher embedding capacity can be achieved with our proposed one. The numerical results are provided to show the performances of the proposed scheme in different cases of bit-plane partition and MSB prediction.

Fuzzy Localization of Steganographic Flipped Bits via Modification Map

Adaptive steganography has become unprecedentedly prevalent compared with non-adaptive ones due to its remarkable performance when resisting modern steganalysis. It prefers hiding bits into pixels from texture regions as such modification is considerably difficult to detect. Current steganalysis capable of locating steganographic payload has only been investigated in the non-adaptive domain, while the works of locating hidden bits modified by adaptive steganographic algorithms have not been studied yet. In this paper, we propose a novel algorithm to locate flipped pixels modified by adaptive steganography in the spatial domain. By re-embedding randomly generated messages upon one single image, we observe that adaptive steganographic methods are prone to modify pixels in the same region, namely texture region. Such property straightforward inspires us to re-embed a random message at the same relative payload into the stego image to obtain the modification map. Then, we extend the modification map with a given margin to locate the modified pixels. The extensive experiments have verified the effectiveness of our designed algorithm in locating flipped pixels modified by the adaptive steganography in the spatial domain.