Embedding Speed Research Articles

A Parallel Framework for Streaming Dimensionality Reduction.

The visualization of streaming high-dimensional data often needs to consider the speed in dimensionality reduction algorithms, the quality of visualized data patterns, and the stability of view graphs that usually change over time with new data. Existing methods of streaming high-dimensional data visualization primarily line up essential modules in a serial manner and often face challenges in satisfying all these design considerations. In this research, we propose a novel parallel framework for streaming high-dimensional data visualization to achieve high data processing speed, high quality in data patterns, and good stability in visual presentations. This framework arranges all essential modules in parallel to mitigate the delays caused by module waiting in serial setups. In addition, to facilitate the parallel pipeline, we redesign these modules with a parametric non-linear embedding method for new data embedding, an incremental learning method for online embedding function updating, and a hybrid strategy for optimized embedding updating. We also improve the coordination mechanism among these modules. Our experiments show that our method has advantages in embedding speed, quality, and stability over other existing methods to visualize streaming high-dimensional data.

Image Steganography Analysis Using GOST Algorithm and PRNG Based on LSB

Security in communication is very important for everyone to pay attention to. To prevent data leakage and illegal retrieval of data, cryptography and steganography can be used. In this study, GOST and XOR LSB with PRNG were used to inject text into images. The final result shows that the combination of these two methods is quite good in terms of image quality, message capacity, embedding speed, and imperceptibility (cannot be seen with the naked eye). Of the 9 image formats tested, 7 images containing messages could be extracted properly with a median MSE of 0.0001935 and a median of PSNR of 85.261. Then, in terms of rotation, all im-age rotations from 90°, 180°, and 270° fail to extract messages and in terms of resizing all sizes from 10%, 30%, 50%, and 80% also fail to extract messages. The average time required for encryption with test data 6 test data is 0.073 seconds with the GOST algorithm, using GOST + XOR LSB with PNRG is 0.485 seconds. By using the XOR combination method LSB with PRNG can store an average of 43.3 bits. From the impercibility test using 5 respondents and visualization using an RGB histogram, it can be seen that there is no difference be-tween the cover image and the stego image.

Distributed parallel genetic algorithm for online virtual network embedding

SummaryNetwork virtualization (NV) has emerged as a promising paradigm to address the constraints of implementing new protocols and services in existing network architecture by allowing the simultaneous coexistence of multiple heterogeneous virtual networks on a shared substrate infrastructure. Hence, NV is a critical technology for establishing future network architectures (e.g., 5G network and the smart Internet of Things [IoT]). Virtual network embedding (VNE) is a major challenge in NV since it is acknowledged as ‐hard. Many VNE solutions have been proposed over the past decade. However, the proposed solutions merely centralize VNE node mapping while recommending virtual link embedding for the shortest path method or multicommodity flow (MCF) mechanism. This research paper presents an intelligent virtual network orchestration based on genetic algorithm (GA) for the link mapping stage that implements distributed parallelism to significantly and efficiently reduce the operation time. Our extensive simulations have demonstrated that the proposed algorithm not only outperforms the state‐of‐the‐art VNE algorithm in all performance metrics but also achieves 44.01% faster embedding speed than the most well‐known, fastest link mapping method in VNE.

FPGA Implementation of Image Steganography Algorithm using Modified LSB Technique

Steganography is one of the most efficient data hiding techniques,where a secret message is embedded in a cover image in such away that only the cover image is visible and at the receiver, thehidden message is extracted from the stego-image. In this paper, amodified Least Significant Bit (LSB) technique is proposed andapplied to different grayscale cover images in a spatial domain.Furthermore, the proposed algorithm is implemented using FPGA,which provides a least embedding time, a faster programmable andcommercial hardware solution for secure communication. Theobtained results prove that, the proposed algorithm has lowcomputational complexity, high embedding speed and the capabilityof embedding a large payload capacity compared to otheralgorithms that implemented in low cost embedded systemapplications.

Improved Processing Speed for Text Watermarking Algorithm in Color Images

Copyright protection and ownership proof of digital multimedia are achieved nowadays by digital watermarking techniques. A text watermarking algorithm for protecting the property rights and ownership judgment of color images is proposed in this paper. Embedding is achieved by inserting texts elements randomly into the color image as noise. The YIQ image processing model is found to be faster than other image processing methods and hence it is adopted for the embedding process. An optional choice of encrypting the text watermark before embedding is also suggested (in case required by some applications), where, the text can is encrypted using any enciphering technique adding more difficulty to hackers. Experiments resulted into embedding speed improvement of more than double the speed of other considered systems (such as least significant bit method, and separate color code methods) and fairly acceptable level of peak signal to noise ratio (PSNR) with low mean square error values for watermarking purposes.

An industry-level blu-ray watermarking framework

In this paper, we present our H.264 Blu-ray watermarking framework which operates at bit stream level and preserves the length of the underlying bit stream. Apart from a description of our watermark embedding and detection (and synchronisation) approaches, we discuss the embedding capacity for different exemplary Blu-ray disks based on their bit stream characteristics as well as the robustness of our watermark to H.264 transcoding and resizing. Furthermore, we assess the parallelizability of our embedding approach and the impact of different hard drive configurations on the overall embedding speed, showing that low access times are as relevant as high transfer rates when maximum speedup through parallelization is desired. Lastly, this paper provides a discussion on a variety of design choices and practical issues which arise when designing an industry-level watermarking framework.

Design and implementation of coupled chaotic maps in watermarking

The present paper proposes a multidimensional coupled chaotic map as a pseudo random number generator. Based on an introduced dynamical systems, a watermark scheme is presented. By modifying the original image and embedding a watermark in the difference values within the original image, the proposed scheme overcomes the problem of embedding a watermark in the spatial domain. As the watermark extraction does not require the original image, the introduced model can be employed for practical applications. This algorithm tries to improve the problem of failure of embedding in small key space, embedding speed and level of security.

Fast Matrix Embedding by Matrix Extending

When designing steganographic schemes, matrix embedding is an efficient method for increasing the embedding efficiency that is de- fined as an average number of bits embedded via per change on the cover. Random linear code-based matrix embedding can achieve high embedding efficiency but cost much in computation. In this paper, we propose a method to increase the embedding speed of matrix embedding by extending the matrix via some referential columns. Compared with the original matrix embedding, the proposed method can exponentially reduce the computational complexity for equal increment of embedding efficiency. Experimental results also show that this novel method achieves higher embedding efficiency and faster embedding speed than previous fast matrix embedding methods, and thus is more suitable for real-time steganogaphic systems.

Watermill: An Optimized Fingerprinting System for Databases under Constraints

This paper presents a walermarking/fingerprinting system for relational databases. It features a built-in declarative language to specify usability constraints that watermarked data sets must comply with. For a subset of these constraints, namely, weight-independent constraints, we propose a novel watermarking strategy that consists of translating them into an integer linear program. We show two watermarking strategies: an exhaustive one based on integer linear programming constraint solving and a scalable pairing heuristic. Fingerprinting applications, for which several distinct watermarks need to be computed, benefit from the reduced computation time of our method that precomputes the watermarks only once. Moreover, we show that our method enables practical collusion-secure fingerprinting since the precomputed watermarks are based on binary alterations located at exactly the same positions. The paper includes an in-depth analysis of false-hit and false-miss occurrence probabilities for the detection algorithm. Experiments performed on our open source software WATERMILL assess the watermark robustness against common attacks and show that our method outperforms the existing ones concerning the watermark embedding speed.