Significant Bit Research Articles

Significance of Least Significant Bits in Digital Image Processing

Digital image processing is one of the vital areas in today’s era. It has numerous applications in various sectors. Bit slicing is important concept in digital image processing. In most of the literature importance has been given to most significant bit (MSB) because it contains more information. This paper presents importance of least significant bit (LSB) in various applications. Keywords: - least significant bit, LSB, bit slice

A Password and Least Significant Bit Substitution Based Steganography Technique for Image Hiding

The proposed work introduces an image steganography technique using text-based password that acts as the symmetric key of encryption and decryption. It contains two components, an encoder, and a decoder. An encoder takes a secret image that needs to be hidden inside another cover image. The Combined image is encrypted with an eight characters’ password. The starting position of the cover image from where the secret image starts to hide depends on the password. Then the (Least Significant Bit) LSB Substitution technique is used to hide the entire secret image inside the cover image. The decoder takes the encrypted image and the password to retrieve the secret image back. The proposed work produces an encrypted image by keeping 99% information of the cover image and 100% information of the secret image, thus it provides lossless retrieval of the secret image. The proposed work includes dynamicity of position in steganography that ensures more security of image data over the network than the existing state of art methods.

An Improved Design of Absolute-value Detector by Using Optimized Ripple Adder

Absolute-value detector (AVD) is one of the most basic bit-operating devices, which compares the magnitude of two inputs. However, the traditional 4-bit AVD is not only time-consuming but also has a high energy consumption. This paper uses a hybrid design to optimize the 4-bit AVD by introducing an improved ripple adder in the absolute value extraction part, which then can be less energy-consuming and requires fewer transistors. The paper divides the design of AVD into an absolute value extraction part and a comparator. The input (2’s complement) can be positive or negative numbers in the absolute value extraction part. By observing the most significant bit (MSB) of the input, the design can determine the sign of input and output magnitude. For the comparator, this paper uses a logic of step-by-step comparison from the most to the least significant bits. Then, this paper finds the minimum delay of the design by critical path analysis and gate sizing. The final delay is set at 1.5 times its minimum. Device voltage optimization is applied for calculating the energy consumption. Finally, with 1.5 times the minimum delay, the energy consumption is 40% less than the consumption when the delay is the minimum.

An Image Steganographic Scheme Based on Edge Detection and Least Significant Bit Substitution

<p>This work presents a steganographic scheme based on Laplacian-of-Gaussian (LoG) edge detection and least significant bit (LSB) substitution. The cover image is first divided into continuous and non-overlapping 4×4-pixel blocks. The pixel at the top left corner of each block (first pixel) is defined as the reference pixel. After the LoG edge detection, the blocks are classified as edge or non-edge blocks, and this information is embedded in the reference pixels. Each non-reference pixel is then embedded with 5 bits and 4 bits of cipher text if it belongs to an edge block or non-edge block, respectively. Compared to the method of Tseng and Leng, Bai et al., and Ghosal et al., proposed method increased the capacity by 39.6%, 7.3%, and 42.7%, respectively, in the “Lena” cover image. To test the generalizability of our method, an embedding capacity and image quality test were conducted using 10,000 512 × 512 sized greyscale images from the BOSSBase dataset. Compared to the aforementioned previous methods, our method improved the capacity by 33.9%, 2.7%, and 36.1%, respectively, while maintaining an acceptable stego-image quality. Finally, proposed method can resist the detection of RS, pixel difference histogram analysis and second order SPAM features.</p> <p> </p>

XCRYPT: Accelerating Lattice-Based Cryptography With Memristor Crossbar Arrays

This paper makes a case for accelerating lattice-based post quantum cryptography with memristor-based crossbars. We map the polynomial multiplications in a representative algorithm, SABER, and show that analog dot-products can yield 1.7 − 32.5× performance and energy efficiency improvement, compared to recent hardware proposals. We introduce several additional techniques to address the bottlenecks in this initial design. First, we show that software techniques used in SABER, that are effective on CPU platforms, are unhelpful in crossbars. Relying on simpler algorithms further improves our efficiency by 1.3 − 3.6×. Second, modular arithmetic in SABER offers an opportunity to drop most significant bits, enabling techniques that exploit a few variable precision ADCs, and yielding up to 1.8× higher efficiency. Third, to further reduce ADC pressure, we propose a simple analog Shift-and-Add technique, demonstrating a 1.3 − 6.3× improvement. Overall, XCRYPT achieve 3 − 15× higher efficiency over the initial design and highlight the importance of algorithm-accelerator co-design.

A Hybrid Approach for Data Hiding using Twofish Algorithm and Compression Steganography Techniques

Data compression and encryption are essential components of information security, facilitating efficient data handling, reduced storage requirements, and secure data transmission. The system presents a novel hybrid data compression algorithm that combines lossy and lossless compression techniques, along with Twofish cryptography. The hybrid approach leverages the strengths of different compression techniques. First, the Huffman coding algorithm is employed to compress textual data efficiently. Subsequently, the cover image undergoes lossy compression using the Discrete Wavelet Transform (DWT) technique. To fortify data security, the Twofish algorithm offers robust and high-level encryption. The encrypted data is then embedded into the compacted cover image using the least significant bit (LSB) technique in a steganographic manner. In the evaluation phase, the system's performance is assessed using key metrics, bits per pixel, mean squared error (MSE), peak signal-to-noise ratio (PSNR), and structural similarity index (SSIM). Comparative analysis with existing methodologies demonstrates the superior performance and methodological efficiency of the system. The results indicate that the hybrid approach strikes a balance between compression efficiency and data security, enabling faster data transmission over limited bandwidth connections and effectively utilizing storage media.

Frequency diversity of the power line time service system

A frequency diversity technique is proposed for OFDM-modulated power line time service systems, and a variety of frequency diversity reception processing schemes are investigated to address the problem of interference caused by power line channel noise. Simulation results show that selecting the appropriate frequency diversity order can effectively reduce the system received signal bit error rate, while using the maximum ratio combining diversity reception scheme has the best effect on improving the system bit error rate performance.

Single‐mode optical fibre digital decoder based on polarization using a K‐nearest neighbour algorithm

AbstractIt is shown experimentally a new digital optical decoding scheme based on the transmission or polarized light at p polarization planes using a K‐Nearest Neighbour (KNN) algorithm through a single‐mode optical fibre at 633 nm. The optical power signal is sent at p polarization planes which constitute p classes required for signal bit recognition. Results show that it is possible to recognize 32 polarizations planes, 5 bits, using 4 features corresponding to the measurement of optical power at 4 different angles at the photodetector side with an average assertiveness of 99.02%.

Hiding a Secret Message Encrypted by S-DES Algorithm

Nowadays, it is quite usual to transmit data through the internet, making safe online communication essential and transmitting data over internet channels requires maintaining its confidentiality and ensuring the integrity of the transmitted data from unauthorized individuals. The two most common techniques for supplying security are cryptography and steganography. Data is converted from a readable format into an unreadable one using cryptography. Steganography is the technique of hiding sensitive information in digital media including image, audio, and video. In our proposed system, both encryption and hiding techniques will be utilized. This study presents encryption using the S-DES algorithm, which generates a new key in each cycle to increases the complexity of the algorithm detection. An additional shared key between the sender and the receiver is added which is applied before starting the encryption process, that key must be hex-decimal in order to increase the level of security and give enough time to delay the guessing of the secret text by the attackers. The secret message data is concealed using one of the two techniques: either least significant bit (3-LSB) steganography or hiding in green and blue bits. To expedite the concealment process, the cover image is enhanced by applying a median filter, the median filter removes noise from the image while preserving its details. Finally, comparing the results of the two methods to determine which is better for the cover image in terms of PSNR metrics and hiding process time.

WELDP: Weighed Edge Local Directional Pattern for expression recognition from facial images

At present, the local appearance-based texture descriptors in Facial Expression Recognition have limited accuracy due to the inability to encode the discriminative edges. The major cause is the presence of distorted and weak edges due to noise. Hence, this paper proposes new Expression Descriptor called as Weighted Edge Local Directional Pattern (WELDP) which can discriminate the weak and strong edges. Unlike the conventional local descriptors, WELDP searches for the support of neighbor pixels in the determination of Facial expression attributes such as Edges, Corners, Lines, and Curved Edges. WELDP encodes only Strong edge responses and discards weaker edge responses after extracting them through edge detection masks. This work adapted two masks for edge detection: they are Robinson Compass Mask and Kirsch Compass Mask. Moreover, the WELDP aims at code redundancy and encode each pixel only with seven bits (one sign bit and six directional bits). Then the WELDP image is described by a histogram and then processed through SVM (Support Vector Machine) for expression identification. From the simulation experiments, the proposed WELDP is found as better than several existing methods.

A new steganography technique based on genetic algorithm

As technology grows, it affect our daily lives becomes more penetrating. Our private information may be violated when communications media are used, to achieve information security this paper was based on a new technique of steganography using cryptography, color model and genetic algorithm. First, the secret text was encrypted with the advanced encryption standard (AES) algorithm. Second, the hiding was applied in two stages. First, the cover-image was converted in to the hue saturation intensity (HSI) color model and select one of the models, then divide it into a group of blocks and hiding the text in them by using least significant bit (LSB) method on specified bytes randomly, then using the genetic algorithm that calculates peak signal-to-noise-ratio (PSNR) for all blocks after the hiding process and thus obtain the best value for PSNR for the optimal block. Second, includes the final hiding of all blocks based on the results of the first stage of the best random distribution of bytes according to the results of the genetic algorithm. The PSNR and mean square error (MSE) measures were adopted to prove the accuracy and efficiency of the results.

A Huffman code LSB based image steganography technique using multi-level encryption and achromatic component of an image

In the recent couple of years, due to the accelerated popularity of the internet, various organizations such as government offices, military, private companies, etc. use different transferring methods for exchanging their information. The Internet has various benefits and some demerits, but the primary bad mark is security of information transmission over an unreliable network, and widely uses of images. So, Steganography is the state of the art of implanting a message in the cover objects, that nobody can suspect or identify it. Therefore, in the field of cover steganography, it is very critical to track down a mechanism for concealing data by utilizing different blends of compression strategies. Amplifying the payload limit, and robustness, and working on the visual quality are the vital factors of this research to make a reliable mechanism. Different cover steganography research strategies have been recommended, and each adores its benefits and impediments but there is a need to foster some better cover steganography implements to accomplish dependability between the essential model of cover steganography. To handle these issues, in this paper we proposed a method in view of Huffman code, Least Significant Bits (LSB) based cover steganography utilizing Multi-Level Encryption (MLE) and colorless part (HC-LSBIS-MLE-AC) of the picture. It also used different substitution and flicking concepts, MLE, Magic matrix, and achromatic concepts for proving the proficiency, and significance of the method. The algorithm was also statistically investigated based on some Statistical Assessment Metrics (SAM) such as Mean Square Error (MSE), Peak Signal Noise Ratio (PSNR), Normalized Cross Correlation (NCC), Structural Similarity Index Metric (SSIM), etc. and different perspectives. The observational outcomes show the likelihood of the proposed algorithm and the capacity to give unwavering quality between security, payload, perception, computation, and temper protection.

Linear Feedback Shift Registers-Based Randomization for Image Steganography

Steganography involves concealing information by embedding data within cover media and it can be categorized into two main domains: spatial and frequency. This paper presents two distinct methods. The first is operating in the spatial domain which utilizes the least significant bits (LSBs) to conceal a secret message. The second method is the functioning in the frequency domain which hides the secret message within the LSBs of the middle-frequency band of the discrete cosine transform (DCT) coefficients. These methods enhance obfuscation by utilizing two layers of randomness: random pixel embedding and random bit embedding within each pixel. Unlike other available methods that embed data in sequential order with a fixed amount. These methods embed the data in a random location with a random amount, further enhancing the level of obfuscation. A pseudo-random binary key that is generated through a nonlinear combination of eight Linear Feedback Shift Registers (LFSRs) controls this randomness. The experimentation involves various 512x512 cover images. The first method achieves an average PSNR of 43.5292 with a payload capacity of up to 16% of the cover image. In contrast, the second method yields an average PSNR of 38.4092 with a payload capacity of up to 8%. The performance analysis demonstrates that the LSB-based method can conceal more data with less visibility, however, it is vulnerable to simple image manipulation. On the other hand, the DCT-based method offers lower capacity with increased visibility, but it is more robust.

A new paradigm for high-capacity reversible data hiding with pixel repetition and adaptive embedding

Reversible data hiding (RDH) offers a useful attribute of retaining the visual semantics with security properties, for the effective management and protection of digital images with their metadata. This paper introduces a Reversible Data Hiding (RDH) scheme with Pixel Repetition (PR) to selectively embed additional secret data. bits utilizing the image redundancy created with PR. A generalized framework of PR is first developed and the rate–distortion criterion is extended for adaptive embedding. An input image is defined to be scaled-up by replacing each original pixel (called seed) with a block of shape s×s containing the seed, where s is the scaling factor. For better utilizing this PR-based image redundancy, we then propose an RDH scheme with two-phase embedding for s=2. The first phase of the scheme embeds 4-bit data in each 2 × 2 image block using a mapping function, which is designed to modify the repeated pixels, keeping the seed intact in each block. Being invertible, the mapping function also allows another phase of embedding in the preserved seeds using an adaptive selection of their least significant bits. Compared to the prominent PR-based and other related schemes, an impressive rate–distortion performance of the proposed scheme is recorded with a greater potential for the applications that require a high and varying embedding rate with better image quality.

W-AMA: Weight-aware Approximate Multiplication Architecture for neural processing

This paper presents the Weight-aware Approximate Multiplication Architecture (W-AMA) for Deep Neural Networks (DNNs). Considering the Gaussian-like weight distribution, it deploys an accuracy-configurable computing component to improve the computational efficiency. Two techniques for effectively integrating the W-AMA into DNN accelerator are presented: (1) A Cartesian Genetic Programming (CGP) based approximate multiplier is designed and selectable to compute the Least Significant Bit (LSB) for a higher accuracy mode. The Reward–Penalty-Coefficient (RPC) is proposed to achieve the internal-compensation. (2) The Hessian-Aware-Approximation (HAA) method is utilized for hybrid approximate modes cross-layer mapping. Based on the W-AMA, an energy-efficient DNN accelerator is proposed and evaluated on 28 nm technology. It can achieve the energy efficiency of 9.6 TOPS/W, and the computational energy efficiency can be improved by 1.5× compared with the standard units, with an 0.52% accuracy loss on CIFAR-10 using ResNet-18.

An unsolvable pixel reduced authentication method for color images with grayscale invariance

This paper introduces an advanced grayscale-invariant authentication method for color images. Prior work directly utilizes the most significant bits (MSBs) of the red and blue channels for authentication code generation and embeds these codes into the least significant bits (LSBs). Concurrently, the green channel is adjusted to sustain consistent grayscale values. However, this direct utilization of MSBs often leads to a decline in image quality and results in a significant number of unsolvable pixels. To address these challenges, we present a new approach specifically designed to combat the deterioration of image quality and the prevalence of unsolvable pixels. In our method, we propose the MSB alteration (MSBA) technique, which modifies the MSBs of the red and blue channels to generate authentication codes with minimal distortion. This technique effectively reduces image distortion and the number of unsolvable pixels. Furthermore, we introduce the pixel substitution strategy (PSS) and the constraint-reduced strategy (CRS) to enhance the embedding efficiency. Experimental results demonstrate that our method outperforms prior work by converting more unsolvable pixels to solvable ones and achieving better detection results. Moreover, our method enhances image quality by approximately 1.5 dB, while maintaining the same embedding capacity.

Memory Carousel: LLVM-Based Bitwise Wear Leveling for Nonvolatile Main Memory

Emerging non-volatile memory yields, alongside many advantages, technical shortcomings, such as reduced cell lifetime. Although many wear-leveling approaches exist to extend the lifetime of such memories, usually a trade-off for the granularity of wear-leveling has to be made. Due to iterative write schemes (repeatedly sense and write), wear-out of memory in certain systems is directly dependent on the written bit value and thus can be highly imbalanced, requiring dedicated bit-wise wear-leveling. Such a bit-wise wear-leveling so far has only be proposed together with a special hardware support. However, if no dedicated hardware solutions are available, especially for commercial off-the-shelf systems with non-volatile memories, a software solution can be crucial for the system lifetime. In this work, we propose entirely software-based bit-wise wearleveling, where the position of bits within CPU words in main memory is rotated on a regular basis. We leverage the LLVM intermediate representation to adjust load and store operations of the application with a custom compiler pass. Experimental evaluation shows that the lifetime by applying local rotation within the CPU word can be extended by a factor of up to 21×. We also show that our method can incorporate with coarser-grained wear-leveling, e.g. on block granularity and assist achievement of higher lifetime improvements.

11 b 200 MS/s 28‐nm CMOS 2b/cycle successive‐approximation register analogue‐to‐digital converter using offset‐mismatch calibrated comparators

AbstractThis letter presents an 11 b 200 MS/s 28 nm CMOS 2b/cycle successive‐approximation register (SAR) analogue‐to‐digital converter (ADC). The offset calibration technique is proposed to reduce the comparator offset mismatch that degrades the linearity of the high‐resolution 2b/cycle SAR ADC. The offset mismatch is reduced to within 0.25 least significant bit (LSB) by generating a compensation voltage from capacitor‐resistor (C‐R) hybrid digital‐to‐analogue converters (DACs). The prototype ADC implemented in a 28‐nm CMOS process demonstrates measured differential and integral non‐linearities within 0.6 LSB and 1.73 LSB at 11 b resolution, respectively. The measured signal‐to‐noise‐and‐distortion ratio (SNDR) and spurious‐free dynamic range (SFDR) are 50.9 dB and 66.2 dB at Nyquist, respectively. The prototype ADC occupies an active die area of 0.115 mm2 and consumes 3.98 mW at a 1.1‐V supply voltage.

Model-Aware XGBoost Method Towards Optimum Performance of Flexible Distributed Raman Amplifier

Toward the next-generation ultra-long-haul optical network, an extremely gradient boosting (XGBoost)-aided machine learning (ML) model is proposed to maximize the flexibility and uniformity in the performance of distributed Raman amplifier (DRA). In order to achieve an accurate prediction of desired signal gain spectrum and bit error rate (BER), a novel decision-tree based system is employed against inconsistent dimensionality between pump frequency and power. The impact of various model evaluation techniques: mean squared error (MSE), coefficient of determination (R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ), root mean square measured data ratio (RSR) and the Nash-Sutcliffe coefficient (NSE) are discussed in detail. It is shown that the proposed method can diagnose the fault within 2.3 ms with accuracy of 99.6% and has also the highest estimation and efficacy in comparison with other ML based tree models. The reported work transforms the successful implementation of XGBoost model to estimate the desired gain profile and BER of DRA in low-loss optical wavelength region (1260-1650nm).

Crypto-Stegano Color Image Based on Rivest Cipher 4 (RC4) and Least Significant Bit (LSB)

Rivest Cipher 4 (RC4) has the main factors that make this algorithm widely used, namely its speed and simplicity, so it is known to be easy for efficient implementation. The nature of the key in the RC4 algorithm is symmetrical and performs a plain per digit or byte per byte encryption process with binary operations (usually XOR) with a semirandom number. To improve the visual image after the encryption process, in this article we use the Least Significant Bit (LSB). In this study, the quality of the stego image and the original image has been calculated using MSE, PSNR and Entropy. Experiments were carried out by images with a size of 128x128 pixels to 2048x2048 pixels. Experiments using imperceptibility prove that the stego image quality is very good. This is evidenced by the image quality which has an average PSNR value above 53 dB, while the lowest PSNR value is 48 dB with a minimum dimension of 128x128 pixels.