This paper conducts a comprehensive cryptanalysis of a novel image cryptosystem, namely NIC, from three distinct perspectives, uncovering several inherent vulnerabilities within the scheme. Unlike most existing cryptanalysis methods that rely on a single approach, this study presents three innovative attack strategies tailored to the specific flaws of NIC. The first attack exploits the equivalence between multi-level and single-level diffusion processes in NIC, revealing the inefficiency of its diffusion mechanism. The second strategy leverages the synthesis and decomposition properties of base images, taking advantage of the scheme’s same-type diffusion operations. The third and most significant contribution is the introduction of the plaintext-to-ciphertext sensitivity (S-PTC) attack, a novel approach initially proposed in this work. Departing from the conventional focus on ciphertext-to-plaintext sensitivity (S-CTP), this study emphasizes S-PTC, an often-neglected aspect of cryptosystem security. By highlighting the fatal flaw of low S-PTC in NIC, the study exposes a critical weakness overlooked in previous research. Furthermore, an in-depth analysis demonstrates that the S-PTC attack is not confined to NIC but can be extended to other general cryptosystems with similar algorithmic structures. Rigorous theoretical derivations and experimental validations have been conducted to confirm the effectiveness and feasibility of all three proposed attacks, providing significant insights into the security evaluation of image encryption schemes.

Abstract This paper introduces a novel approach called Chebyshev mapping and strongly connected topology for optimization of echo state network (ESN). To enhance the predictive performance of ESNs for time series data, Chebyshev mapping is employed to optimize the irregular input weight matrix. And the reservoir of the ESN is also replaced using an adjacency matrix derived from a digital chaotic system, resulting in a reservoir with strong connectivity properties. Numerical experiments are conducted on various time series datasets, including the Mackey–Glass time series, Lorenz time series and solar sunspot numbers, validating the effectiveness of the proposed optimization methods. Compared with the traditional ESNs, the optimization method proposed in this paper has higher predictive performance, and effectively reduce the reservoir’s size and model complexity.

Developers often seek solutions for their programming problems by retrieving existing questions on technical Q&A sites such as Stack Overflow. In many cases, they fail to find relevant questions due to the knowledge gap between the questions and the queries or feel it hard to choose the desired questions from the returned results due to the lack of explanations about the relevance. In this paper, we propose KGXQR, a knowledge graph based explainable question retrieval approach for programming tasks. It uses BERT-based sentence similarity to retrieve candidate Stack Overflow questions that are relevant to a given query. To bridge the knowledge gap and enhance the performance of question retrieval, it constructs a software development related concept knowledge graph and trains a question relevance prediction model to re-rank the candidate questions. The model is trained based on a combined sentence representation of BERT-based sentence embedding and graph-based concept embedding. To help understand the relevance of the returned Stack Overflow questions, KGXQR further generates explanations based on the association paths between the concepts involved in the query and the Stack Overflow questions. The evaluation shows that KGXQR outperforms the baselines in terms of accuracy, recall, MRR, and MAP and the generated explanations help the users to find the desired questions faster and more accurately.

AI applications often use ML/DL (Machine Learning/Deep Learning) models to implement specific AI tasks. As application developers usually are not AI experts, they often choose to integrate existing implementations of ML/DL models as libraries for their AI tasks. As an active research area, AI attracts many researchers and produces a lot of papers every year. Many of the papers propose ML/DL models for specific tasks and provide their implementations. However, it is not easy for developers to find ML/DL libraries that are suitable for their tasks. The challenges lie in not only the fast development of AI application domains and techniques, but also the lack of detailed information of the libraries such as environmental dependencies and supporting resources. In this paper, we conduct an empirical study on ML/DL library seeking questions on Stack Overflow to understand the developers' requirements for ML/DL libraries. Based on the findings of the study, we propose a task-oriented ML/DL library recommendation approach, called MLTaskKG. It constructs a knowledge graph that captures AI tasks, ML/DL models, model implementations, repositories, and their relationships by extracting knowledge from different sources such as ML/DL resource websites, papers, ML/DL frameworks, and repositories. Based on the knowledge graph, MLTaskKG recommends ML/DL libraries for developers by matching their requirements on tasks, model characteristics, and implementation information. Our evaluation shows that 92.8% of the tuples sampled from the resulting knowledge graph are correct, demonstrating the high quality of the knowledge graph. A further experiment shows that MLTaskKG can help developers find suitable ML/DL libraries using 47.6% shorter time and with 68.4% higher satisfaction.

'Hearables' have become important in the aging population. This study investigates whether smart technologies help middle-aged and elderly people accept hearing aid devices in smart cities of China. The authors adopt the PLS-SEM framework to analyze the factors that affect behavioral intention towards adopting hearing aids in smart cities. In order to avoid common method bias, Harman's single factor method is also carried out to make sure the instrument does not introduce a bias. The findings suggest that perceived playfulness and perceived usefulness are principal determinants of hearing aids adoption. In contrast, perceived ease of use, a factor always stressed in literature, does not matter significantly. The results reveal that smart technologies enable patients to access professional services and instructions playfully, which reduces obstacles to adopt hearing aids. This study provides novel insights for policymakers and manufacturers to expand hearing aid adoption by facilitating smart infrastructure and technologies.

TripletGAN is a variant of Generative Adversarial Network (GAN) by replacing the classification loss of discriminator with a triplet loss. Although TripletGAN delivers better mode coverage than vanilla GAN thanks to the characteristics of adversarial triplet loss that maximizes the embedding distance between generated samples, its adversarial training method suffers from the drawback that some generated images tend to deviate from the real sample distribution and noisy images are produced as we increase the number of iterations of training. In this paper, we propose an adversarially balanced triplet loss with four dynamic coefficients to achieve a trade-off between the quality and the diversity of generated samples. We also design a novel network architecture to provide GANs with an auto-encoding ability. Extensive experiments demonstrate the effectiveness of our proposed methods in terms of alleviating the problem in TripletGAN and the superiority in terms of reconstruction over some methods that directly train generator and encoder such as O-GAN.

This paper aims to refine and expand the theoretical and application framework of higher-dimensional digital chaotic system (HDDCS). Topological mixing for HDDCS is strictly proved theoretically at first. Topological mixing implies Devaney's definition of chaos in a compact space, but not vice versa. Therefore, the proof of topological mixing promotes the theoretical research of HDDCS. Then, a general design method for constructing HDDCS via loop-state contraction algorithm is given. The construction of the iterative function uncontrolled by random sequences (hereafter called iterative function) is the starting point of this research. On this basis, this paper put forward a general design method to solve the construction problem of HDDCS, and several examples illustrate the effectiveness and feasibility of this method. The adjacency matrix corresponding to the designed HDDCS is used to construct the chaotic Echo State Network (ESN) for predicting Mackey-Glass time series. Compared with other ESNs, the chaotic ESN has better prediction performance and is able to accurately predict a much longer period of time.

This paper initiates a systematic methodology for real-time chaos-based video encryption and decryption communications on the system design and algorithm analysis. The proposed system design and algorithm analysis have been validated on an FPGA hardware platform via Verilog Hardware Description Language (Verilog HDL). Based on the fundamental anti-control principles of dynamical systems, a 6-D real domain chaotic system is designed, and then the corresponding Verilog HDL algorithm is developed. The proposed Verilog HDL algorithm is utilized to design a real-time chaos-based secure video communication system, with a generalized design principle derived, which is implemented on an FPGA hardware platform equipped with an XUP Virtex-II chip. Following this line, the designed working mechanism is demonstrated by hardware experiments. The security performance is tested using the TESTU01 statistical test suites, the differential analysis, and the sensitivity of key parameters mismatch. Both theoretical analysis and experimental results validate the feasibility and reliability of the proposed system.

A systematic methodology is proposed for a chaotic map-based real-time video encryption and decryption system with advanced Reduced Instruction Set Computer machine (ARM)-embedded hardware implementation. According to the anticontrol principle of dynamical systems, first, an 8-D discrete-time chaotic map-based system is constructed, which possesses the required property of 1-1 surjection in the integer range$[{0,\,N-1}]$, where$N$is the number of frame pixels, suitable for position scrambling of each video frame. Then, an 8-D discrete-time hyperchaotic system is designed for encryption–decryption of red, green, and blue (RGB) tricolor pixel values. Using the ARM-embedded platform super4412 model with Cortex-A9 processor, together with the standard QT cross-platform, an integrated chaotic map-based real-time secure video communication system is designed, implemented, and evaluated. In addition, the security performance of the designed system is tested using criteria from the National Institute of Standards and Technology statistical test suite. The main feature of this method is that, both scrambling–antiscrambling of RGB tricolor pixel positions and encryption–decryption of pixel values are realized simultaneously for enhancing the security. As is well known, compared with numerical simulations, hardware implementation for such a secure video communication system is very difficult to achieve, but we successfully implemented and tested in a real-world network environment. Both theoretical analysis and experimental results validate the feasibility and real-time performance of the new secure video communication system.

In this brief, we consider the problem of blind identification in underdetermined instantaneous mixture cases, where there are more sources than sensors. A new blind identification algorithm, which estimates the mixing matrix in a sequential fashion, is proposed. By using the rank-1 detecting device, blind identification is reformulated as a constrained optimization problem. The identification of one column of the mixing matrix hence reduces to an optimization task for which an efficient iterative algorithm is proposed. The identification of the other columns of the mixing matrix is then carried out by a generalized eigenvalue decomposition-based deflation method. The key merit of the proposed deflation method is that it does not suffer from error accumulation. The proposed sequential blind identification algorithm provides more flexibility and better robustness than its simultaneous counterpart. Comparative simulation results demonstrate the superior performance of the proposed algorithm over the simultaneous blind identification algorithm.

Over the last two decades, multi-scroll chaos generation has seen promising advances and becomes an active research field. This paper initiates a novel approach to design various grid multi-wing butterfly chaotic attractors from piecewise Lü system based on switching control and heteroclinic orbit. It should be especially pointed out that these generating multi-wing chaotic attractors are chaotic in the sense of Smale horseshoe from Shilnikov theorem. Moreover, there are some potential engineering applications in the future because of the simplicity of the proposed design approach.

The wide application of Binary segmentation for grayscale images could be found in computer vision and pattern recognition, especially for the purpose of object identification and recognition with industry and military images. This paper proposes a noise robust binary segmentation approach which incorporates Ant Colony System (ACS) with the modified Fuzzy C-Means (FCM) clustering algorithm. The ACS first survey the whole image, adding an additional pheromone dimension other than grayscale on each pixel. The modified FCM then deems every pixel a 2-dimensional vector and classifies all image pixels into two categories. Experiments have demonstrated better segmentation results and the advantage of robustness against noise using this method.

This paper proposes a novel multiscroll chaotic system, which is different from Chua’s circuit and all its variants in most aspects of the algebraic form, circuit design, and geometrical structure of the attractor. In particular, the multiscroll attractor of this new system is more complex than that of the generalized Chua’s circuit when they both have the same number of scrolls. The dynamical behaviors of the new system are then analyzed, including the bifurcation diagram and the Lyapunov exponent spectra. Moreover, a module-based circuit diagram is designed for realizing various multiscroll attractors. Finally, experimental circuits are implemented with physical observations reported.

Based on the sawtooth wave function, this paper initiates an approach for generating novel multi-wing butterfly chaotic attractors from the generalized first and second types of modified Lorenz systems. Our theoretical analysis shows that every index-2 saddle-focus equilibrium corresponds to a unique wing in the butterfly attractors. Compared with the traditional ring-shaped multiscroll Lorenz chaotic attractors, the proposed multi-wing butterfly chaotic attractors are much easier to be constructed and implemented by analog circuits. Furthermore, a module-based unified circuit diagram is designed for realizing various multi-wing attractors.

In this paper, a general structure based on Chua's circuit framework is proposed for the generation of n×m scroll attractors. Starting from a modified Chua's circuit with n-scroll attractor, n × m-scrolls can be duly generated and observed by adding a simple staircase function onto the state equations. This method is successfully applied to different n-scroll Chua's circuits with equi-distance equilibrium points, and the results are verified by both simulations and experiments.

This paper introduces a novel four-order system, which can generate one-directional (1-D) n-torus, two-directional (2-D) n /spl times/ m-torus, three-directional (3-D) n /spl times/ m /spl times/ l-torus, four-directional (4-D) n /spl times/ m /spl times/ l /spl times/ p-torus chaotic attractors. Furthermore, a novel block circuit diagram is designed for the hardware implementation of multi-directional grid multi-torus chaotic attractors. This is the first time in the literature to experimentally verify a 5 /spl times/ 5 /spl times/ 3 /spl times/ 3-torus chaotic attractors.

A systematic circuit design approach is proposed for experimental verification of hyperchaotic 2, 3, 4-scroll attractors from a generalized Matsumoto-Chua-Kobayashi (MCK) circuit. The recursive formulas for system parameters are rigorously derived for improving the hardware implementation.