Article
Mathematics, Interdisciplinary Applications
Fei Yu, Hui Shen, Zinan Zhang, Yuanyuan Huang, Shuo Cai, Sichun Du
Summary: This study investigates the dynamics of a small neural network with three neurons under electromagnetic radiation, revealing that the strength of the radiation can alter the equilibrium points in the network and lead to diverse attractor trajectories. Various dynamic behaviors were observed, including transitional coexisting attractors, chaos, and intermittent chaos.
CHAOS SOLITONS & FRACTALS
(2021)
Article
Computer Science, Information Systems
Budoor Obid Al-Roithy, Adnan Gutub
Summary: The research focuses on ensuring the security of RGB images during transmission among users using appropriate Pseudo Random Number Generators (PRNG). Our technique involves implementing various PRNG techniques in two consecutive crypto-processes for secure image transformation, aiming to establish suitability and reliability through standard security measures.
MULTIMEDIA TOOLS AND APPLICATIONS
(2021)
Article
Physics, Multidisciplinary
Fei Yu, Zinan Zhang, Hui Shen, Yuanyuan Huang, Shuo Cai, Jie Jin, Sichun Du
Summary: A pseudo-random number generator (PRNG) based on a feedback controller using a Hopfield neural network chaotic oscillator is proposed to suppress chaotic degradation caused by numerical accuracy constraints in FPGA-based neural network systems. The system utilizes the magnetic flux across neuron cell membranes as a feedback condition to disturb other neurons, preventing periodicity. Implementation and synthesis on FPGA using Verilog HDL code, along with simulations on Vivado 2018.3 software, demonstrate high security and randomness in the generated binary data, verified through statistical tests. Additionally, an image encryption and decryption system based on the PRNG design is successfully implemented and validated through simulation and security analysis.
FRONTIERS IN PHYSICS
(2021)
Article
Computer Science, Information Systems
Feng Zhang, Jianeng Tang, Zezong Zhang, Zhongming Huang, Tingting Huang
Summary: This paper proposes a new two-dimensional absolute-cosine chaotic model (ACCM) that can generate chaotic maps with simple structures and complex behaviors based on existing chaotic systems. Experimental results show the effectiveness of the model and its applications in hardware implementation and pseudo-random number generation.
Article
Computer Science, Artificial Intelligence
Hao Ming, Hanping Hu, Jun Zheng
Summary: This paper proposes a structure-varying delay-coupled chaotic model (SVDCCM) with attack immunity and proven chaotic properties. Different coupling structures are investigated to determine their effects on chaotic performance, with loop structures recommended for better chaotic behaviors. General changing principles, including random and fast varying, are proposed as guidance for designing structure-varying systems. Experimental results show that SVDCCM exhibits complex chaotic behaviors, good statistical properties, and high unpredictability. It also demonstrates strong security against various attack challenges. Additionally, a pseudo-random number generator (PRNG) based on SVDCCM is designed and implemented on a hardware platform, with performance tests showing high reliability and unpredictability of the generated binary sequences.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Engineering, Mechanical
Qiujie Wu
Summary: The paper proposes a universal framework called cascade-sine chaotification model (CSCM) for producing diverse chaotic maps with higher complexity and larger chaotic ranges compared to seed maps. The effectiveness of CSCM is verified through systematic analysis of four chaotic maps generated by CSCM, which exhibit robust hyperchaotic properties in a large parameter range. The randomness of the obtained chaotic sequences is demonstrated through the introduction of a pseudo-random number generator (PRNG) in the study.
NONLINEAR DYNAMICS
(2021)
Article
Computer Science, Information Systems
Om Dev Singh, Sangeeta Dhall, Anjali Malik, Shailender Gupta
Summary: This paper proposes an image encryption scheme based on Generative Adversarial Network, utilizing specially designed substitution box, permutation box, and diffusion box for confidentiality. The experiment shows that the proposed scheme outperforms state-of-the-art methods in terms of performance and resistance to attacks.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Engineering, Mechanical
Shijian Cang, Zhijun Kang, Zenghui Wang
Summary: A novel PRNG based on conservative chaotic sequence is proposed, which is validated through numerical investigation for generating high quality chaotic signals. The PRNG algorithm shows advantages of large keyspace, high sensitivity, and good randomness.
NONLINEAR DYNAMICS
(2021)
Review
Multidisciplinary Sciences
Mario Lanza, Abu Sebastian, Wei D. Lu, Manuel Le Gallo, Meng-Fan Chang, Deji Akinwande, Francesco M. Puglisi, Husam N. Alshareef, Ming Liu, Juan B. Roldan
Summary: Memristive devices, which can change their resistance and memory state, have potential applications in various fields. However, there are still challenges to be addressed, including performance and reliability issues.
Article
Computer Science, Hardware & Architecture
Luis Gerardo de la Fraga, Brisbane Ovilla-Martinez
Summary: This paper introduces a pseudo random number generator (PRNG) built with a chaotic map without fixed points using fixed-point arithmetic. The randomness of the generated binary sequences is tested using TestU01 statistical tests. Three multimodal benchmark functions are optimized using the proposed PRNG and compared with the standard random function in C. The paper also presents a hardware design of the PRNG on an FPGA.
INTEGRATION-THE VLSI JOURNAL
(2023)
Article
Computer Science, Information Systems
Rajiv Ranjan Suman, Bhaskar Mondal, Tarni Mandal
Summary: A new algorithm for image encryption using Composite Logistic Sine Map (CLSM) and Secure Hash Algorithm-256 (SHA-256) is proposed for secure transmission and storage of images over insecure public networks. The algorithm was tested and found to be robust, scalable, and suitable for low-power devices.
MULTIMEDIA TOOLS AND APPLICATIONS
(2022)
Article
Engineering, Electrical & Electronic
Cheng-Bin Chen, Tsung Chen, Yu-Hsiang Huang, Yuan-Hao Huang
Summary: This paper proposes FPGA-based RNG and NG based on the chaos system, which utilize Euler method and ADC-noise-perturbated initial values to generate random sequences and generate Gaussian noise signals with parallel Box Muller processors.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
(2023)
Article
Mathematics, Applied
Elena Almaraz Luengo, Bittor Alana Olivares, Luis Javier Garcia Villalba, Julio Hernandez-Castro
Summary: In various fields such as Statistics, Particle Physics, Cryptography, and Computer Security, it is important to obtain long sequences of random numbers. Statistical tests are commonly used to verify the randomness of these sequences. This paper focuses on analyzing the dependencies among the statistical tests in the NIST SP 800-22 suite by conducting experiments using sequences of different lengths and from different entropy sources. The findings are presented in a statistically sound manner, highlighting the significance of test independence and its impact on effectiveness and efficiency.
APPLIED MATHEMATICS AND COMPUTATION
(2023)
Review
Computer Science, Information Systems
Kamalika Bhattacharjee, Sukanta Das
Summary: This paper aims to search for and rank the so-called good generators by conducting a survey and empirical testing of pseudo-random number generators. Different types of generators are classified, and selected widely used ones are tested and ranked based on the results.
COMPUTER SCIENCE REVIEW
(2022)
Article
Engineering, Mechanical
Chunxiao Yang, Ina Taralova, Safwan El Assad, Jean-Jacques Loiseau
Summary: This paper proposes a pseudo-random number generator and image encryption scheme based on fractional chaotic systems. The performance and security analyses show that the proposed system is practical and efficient.
NONLINEAR DYNAMICS
(2022)
Article
Computer Science, Artificial Intelligence
Zhuoqun Xia, Yaling Chen, Bo Yin, Haolan Liang, Hongmei Zhou, Ke Gu, Fei Yu
Summary: This paper proposes an efficient intrusion detection framework Fed_ADBN based on federated attention deep belief network and client selection. It not only protects data security but also accurately detects network attacks in AMI network using a combination of federated learning and attention mechanism.
Article
Engineering, Electrical & Electronic
Fei Yu, Xinxin Kong, Abdulmajeed Abdullah Mohammed Mokbel, Wei Yao, Shuo Cai
Summary: A novel local active and nonvolatile memristor is designed and its memristive properties are verified through circuit experiments. A 4D memristive Hopfield neural network (MHNN) is constructed using this memristor, which can perform complex dynamics and is suitable for image encryption applications.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
(2023)
Article
Mathematics
Fei Yu, Wuxiong Zhang, Xiaoli Xiao, Wei Yao, Shuo Cai, Jin Zhang, Chunhua Wang, Yi Li
Summary: In this paper, a simple seven-term 4D hyperchaotic system based on the classical Sprott-C 3D chaotic system is presented. The system is inspired by a previous study on a simple 4D hyperchaotic system. The paper discusses the limitations of the previous system and proposes an improved 5D memristive hyperchaotic system with hidden attractors. The properties of the new system are analyzed and hardware circuits are realized and verified through experiments.
Article
Mathematics
Yue Zhu, Chunhua Wang, Jingru Sun, Fei Yu
Summary: In this paper, we propose a chaotic digital image encryption scheme based on an optimized artificial fish swarm algorithm and DNA coding to address the problems of small key space and weak resistance to differential attacks in existing encryption algorithms. The key is associated with the ordinary image pixel through the MD5 hash operation, and the hash value generated by the ordinary image is used to increase the sensitivity of the key. The artificial fish school algorithm is used to scramble the positions of pixels in the block, and scrambling operation between blocks is proposed to increase the scrambling effect. Operations based on DNA encoding, obfuscation, and decoding technologies are performed in the diffusion stage to obtain encrypted images.
Article
Computer Science, Hardware & Architecture
Hairong Lin, Chunhua Wang, Cong Xu, Xin Zhang, Herbert H. C. Iu
Summary: In this article, a novel method for designing multistructure chaotic attractors in memristive neural networks is proposed. By utilizing a multipiecewise memristive synapse control in a Hopfield neural network (HNN), various complex multistructure chaotic attractors can be produced. Theoretical analysis and numerical simulation demonstrate that multiple multistructure chaotic attractors with different topologies can be generated by conducting the memristive synapse-control in different synaptic coupling positions. Meanwhile, the number of structures can be easily controlled with the memristor control parameters. Furthermore, a module-based analog memristive neural network circuit is designed, allowing the arbitrary number of multistructure attractors to be obtained by selecting corresponding control voltages. Finally, a novel image encryption cryptosystem with a permutation-diffusion structure is designed and evaluated, exhibiting its excellent encryption performances, especially the extremely high key sensitivity.
IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS
(2023)
Article
Computer Science, Hardware & Architecture
Fei Yu, Si Xu, Xiaoli Xiao, Wei Yao, Yuanyuan Huang, Shuo Cai, Bo Yin, Yi Li
Summary: In this paper, a new 5D memristive exponential hyperchaotic system is proposed and its fundamental dynamics characteristics are analyzed. The system exhibits a rich set of dynamic behaviors when appropriate parameter sets are chosen. The system is implemented using the Field Programmable Gate Array (FPGA) and the experimental results are consistent with the numerical simulation results on MATLAB. An image encryption application based on the system is presented, and the security analysis demonstrates the feasibility and effectiveness of the image encryption algorithm.
INTEGRATION-THE VLSI JOURNAL
(2023)
Article
Computer Science, Hardware & Architecture
Shuo Cai, Caicai Xie, Yan Wen, Weizheng Wang, Fei Yu, Lairong Yin
Summary: With the advancement of microelectronics technology, multiple-node upset (MNU), caused by single-particle and charge-sharing effects, has become one of the most crucial factors affecting chip reliability. This paper introduces a completely self-recoverable TNUCR latch, which consists of interlocked four-input C-elements (CEs) and inverters. It also proposes an improved low-cost TNU completely self-recoverable (LCTNUCR) latch, replacing the inverter with a four-input CE and incorporating a high-speed transmission path (HSTP) for faster self-recovery. Experimental results demonstrate the tolerance and self-recovery capabilities of both latches, with the TNUCR latch achieving a 41.05% reduction in delay-power-area product and the LCTNUCR latch achieving a 71.30% reduction compared to the latest representative TNU hardened latch.
INTEGRATION-THE VLSI JOURNAL
(2023)
Article
Engineering, Electrical & Electronic
Shuo Cai, Yan Wen, Jiangbiao Ouyang, Weizheng Wang, Fei Yu, Bo Li
Summary: In this paper, a cross-coupled 18T SRAM cell (CC18T) is proposed, which reduces power consumption and improves reliability. The simulation results show that CC18T can achieve single-node-upset recovery and partial double-node-upset recovery. Compared with other circuits, CC18T reduces average power consumption by 30% and decreases read and write access time by 9.27% and 10.35% on average.
MICROELECTRONICS JOURNAL
(2023)
Article
Chemistry, Analytical
Shiwen Zhang, Hong Liu, Cheng Sun, Xingjin Wu, Pei Wen, Fei Yu, Jin Zhang
Summary: To effectively detect students' behaviors in the classroom, this study presents a classroom behavior detection model based on an improved SlowFast. The model utilizes a Multi-scale Spatial-Temporal Attention (MSTA) module to extract multi-scale spatial and temporal information, and incorporates Efficient Temporal Attention (ETA) to focus on salient features in the temporal domain. Furthermore, a spatio-temporal-oriented student classroom behavior dataset is constructed. Experimental results demonstrate that our proposed MSTA-SlowFast achieves a better detection performance compared to SlowFast, with a 5.63% improvement in mean average precision (mAP) on the self-made classroom behavior detection dataset.
Article
Chemistry, Multidisciplinary
Chunwei Hu, Xianfeng Liu, Sheng Wu, Fei Yu, Yongkun Song, Jin Zhang
Summary: This research proposes a dynamic graph convolutional network model (Res-DGCN) based on the residual network structure for accurate crowd flow prediction in urban areas. The model utilizes the spatio-temporal attention module (SA) to capture the spatial relationship between target nodes and adjacent nodes, and the conditional convolution module (SCondConv) to learn the shifting characteristics of crowd flow. The proposed model achieves better performance compared to baseline models, with improvements in mean absolute error (MAE) and root mean square error (RMSE).
APPLIED SCIENCES-BASEL
(2023)
Editorial Material
Physics, Multidisciplinary
Fei Yu, Hairong Lin, Viet-Thanh Pham
FRONTIERS IN PHYSICS
(2023)
Review
Mathematics
Hairong Lin, Chunhua Wang, Fei Yu, Jingru Sun, Sichun Du, Zekun Deng, Quanli Deng
Summary: Since the discovery of the Lorenz chaotic system in 1963, the construction of chaotic systems with complex dynamics has been a hot topic in chaos research. Recently, memristive Hopfield neural networks (MHNNs) have shown great potential in designing complex, chaotic systems due to their unique network structures, hyperbolic tangent activation function, and memory property. This review provides an analysis of different modeling methods, reviews pioneering works and recent important papers, and surveys the progress of MHNN-based chaotic systems in various applications. It aims to be a reference and resource for both chaos researchers and those interested in applying chaotic systems.
Article
Engineering, Multidisciplinary
Fei Yu, Hui Shen, Qiulin Yu, Xinxin Kong, Pradip Kumar Sharma, Shuo Cai
Summary: In order to ensure the information security of medical data transmitted in IoT, we propose three new MHNN models using a non-ideal flux-controlled memristor model. These models exhibit complex dynamical behaviors such as coexisting attractors, multi-scroll attractors, and grid multi-scroll attractors. The proposed model is implemented on an FPGA and a complete medical data sharing solution is provided, ensuring timely medical treatment for referral patients and protecting patient privacy.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2023)
Article
Computer Science, Hardware & Architecture
Shuo Cai, Yan Wen, Caicai Xie, Weizheng Wang, Fei Yu
Summary: This paper introduces two radiation-hardened SRAM designs (LPDNUR and HSDNUR) that can self-recover from single-node and double-node upsets. LPDNUR uses a two-input C-element structure to reduce power consumption and transmission delays. HSDNUR uses a combination of NMOS and PMOS as the transistor for one-node data transmission to increase current drive capability and reduce transmission delays. Compared to existing radiation-hardened SRAM designs, LPDNUR reduces average power consumption by 24.59% and HSDNUR reduces read access time by 35.71% and write access time by 24.14% on average.
INTEGRATION-THE VLSI JOURNAL
(2023)
Article
Mathematics, Interdisciplinary Applications
Fei Yu, Qiulin Yu, Huifeng Chen, Xinxin Kong, Abdulmajeed Abdullah Mohammed Mokbel, Shuo Cai, Sichun Du
Summary: In this paper, a fractional-order chaotic system based on a memristive Hopfield neural network model is introduced, and the dynamical behaviors under different orders and coupling strengths are investigated. Additionally, a chaotic audio encryption scheme based on MQTT protocol is proposed and implemented on Raspberry Pi.
FRACTAL AND FRACTIONAL
(2022)
