Article
Physics, Multidisciplinary
Jilei Sun
Summary: This paper proposes an associated color chaotic image encryption algorithm based on a two-dimensional chaotic system and random XOR diffusion. The algorithm generates initial values and key streams, processes color image channels into matrices, and then performs color image scrambling and random XOR diffusion based on the 2D-LSCM mathematical expression.
Article
Engineering, Electrical & Electronic
K. U. Shahna, Anuj Mohamed
Summary: A novel method for symmetric image encryption using Lorenz chaotic system is proposed in this paper, which includes operations such as keystream generation, permutation, and diffusion to achieve higher security. The security of the proposed cryptosystem has been assessed by various evaluation metrics, showing superior performance compared to several state-of-the-art techniques.
SIGNAL PROCESSING-IMAGE COMMUNICATION
(2021)
Article
Engineering, Electrical & Electronic
Yiqun Zhang, Ning Jiang, Anke Zhao, Shiqin Liu, Jiafa Peng, Lu Chen, Martin P. J. Lavery, Hasan T. Abbas, Kun Qiu
Summary: This paper proposes and experimentally demonstrates a novel hybrid chaos-based three-dimensional (3-D) constellation scrambling scheme to simultaneously improve the physical layer security and transmission performance of the coherent optical orthogonal frequency division multiplexing (CO-OFDM) system.
JOURNAL OF LIGHTWAVE TECHNOLOGY
(2022)
Article
Physics, Multidisciplinary
Huijie Zhang, Weizhen Sun, Ling Lu
Summary: In this paper, a chaotic encryption algorithm based on Josephus cycle scrambling diffusion is proposed to break the correlation between data and protect image information. The algorithm generates an adaptive key to resist plaintext attacks and uses Josephus cycle to scramble the ranks of plain-text images and break the strong correlation between pixels. Compared with previous studies, the algorithm has slightly improved average entropy of encrypted images, and it has the advantages of a large key space, high key sensitivity, anti-robust attacks, and feasible encryption efficiency.
FRONTIERS IN PHYSICS
(2023)
Article
Engineering, Electrical & Electronic
Pengbo Liu, Xingyuan Wang, Yining Su, Huipeng Liu, Salahuddin Unar
Summary: This article proposes a new spatiotemporal chaotic system named improved sinusoidal dynamic non-adjacent coupled mapping lattice (ISDNCML) with an infinite parameter range. The performance test shows that ISDNCML has more random lattice interaction, better chaos, and excellent cryptography. Based on the characteristics of ISDNCML, a globally coupled private image encryption algorithm is proposed, which ensures the security of private information by introducing ill-conditioned dynamic diffusion into the private area during encryption. The security and practicability of this cryptographic system are verified through analysis and various tests.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS
(2023)
Article
Optics
Xingyuan Wang, Ruiying Si
Summary: This paper proposes a new chaotic image encryption scheme using dynamic L-shaped scrambling and combined map diffusion, generating chaotic sequences through the 2D He'non system. The algorithm confuses and diffuses the image effectively, providing high security against common attacks with efficient running time.
Article
Mathematics, Interdisciplinary Applications
Xingyuan Wang, Nana Guan, Jingjing Yang
Summary: This paper proposes a chaotic image encryption algorithm based on scrambling and diffusion operations, which uses an improved zigzag method for scrambling and a row-by-row strategy for diffusion. The chaotic sequence used in the encryption operation is generated by a one-dimensional Logistic Self-embedding chaotic system, showing superior security and efficiency in practical application.
CHAOS SOLITONS & FRACTALS
(2021)
Article
Engineering, Electrical & Electronic
Anke Zhao, Ning Jiang, Shiqin Liu, Yiqun Zhang, Kun Qiu
Summary: A novel optical encryption scheme based on private chaotic phase scrambling is proposed in this work, which can effectively protect the security on the physical layer of optical communications. Experimental and numerical results demonstrate that the scheme can efficiently encrypt WDM signals into noise-like signals while providing low latency, high speed, and low hardware cost advantages.
JOURNAL OF LIGHTWAVE TECHNOLOGY
(2021)
Article
Mathematics, Interdisciplinary Applications
Xingyuan Wang, Cheng Liu, Donghua Jiang
Summary: This article proposes a new image encryption scheme that combines new chaotic mapping and parallel compressed sensing. The scheme provides double protection for image content and vision, ensuring both visual and informational security.
CHAOS SOLITONS & FRACTALS
(2022)
Article
Physics, Multidisciplinary
Ting Wang, Bin Ge, Chenxing Xia, Gaole Dai
Summary: This paper proposes a multi-image encryption algorithm based on cascade modulation chaotic system (CMCS), which utilizes block-scrambling-diffusion and non-sequence diffusion to enhance the security of the encryption algorithm.
Article
Computer Science, Information Systems
Yongjin Xian, Xingyuan Wang, Lin Teng, Xiaopeng Yan, Qi Li, Xiaoyu Wang
Summary: This study proposes an iterative method for vectors with fractal characteristics, using the double parameters fractal sorting vector (DPFSV) to control node relationships in spatiotemporal chaotic systems. The new spatiotemporal chaotic system based on DPFSV exhibits better dynamics compared to the coupled map lattice (CML) system. Combining DPFSV and the spatiotemporal chaotic system, a new cryptographic system is constructed to achieve permutation-diffusion synchronous encryption, which proves to have a good encryption effect and resistance to various attacks.
INFORMATION SCIENCES
(2022)
Article
Engineering, Electrical & Electronic
Pengbo Liu, Xingyuan Wang, Yining Su
Summary: This paper proposes a complementary embedding encryption strategy, which replaces the optimal similar area and embeds the airport image into a random position through the complementary embedding algorithm. An improved sine cross coupled mapping lattice (ISCCML) is proposed to generate a better key stream. A fractal disordered matrix (FDM) with iterative and out-of-order properties is presented for the simultaneous scrambling diffusion of images. The results indicate that the proposed scheme can avoid repeated encryption while ensuring the security of important information; the security analysis shows that the algorithm has security, practicality, and scalability.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
(2023)
Article
Physics, Multidisciplinary
Feifei Yang, Xinlei An, Li Xiong
Summary: This work develops a new discrete chaotic map and applies it in an image encryption algorithm. The performance and security features of the proposed algorithm are evaluated, showing promising results in improving image encryption security.
Article
Computer Science, Information Systems
Xiaopeng Yan, Xingyuan Wang, Yongjin Xian
Summary: This paper proposes a new image encryption method based on arithmetic sequence, DNA coding, and chaotic mapping. By utilizing chaotic flow and DNA coding rules, the pixel values are modified, resulting in the destruction and encryption of the original information.
MULTIMEDIA TOOLS AND APPLICATIONS
(2021)
Article
Computer Science, Information Systems
Xiaoyang Chen, Jun Mou, Yinghong Cao, Huizhen Yan, Hadi Jahanshahi
Summary: This paper proposes two hyperchaotic systems and new DNA operation rules for image encryption, thereby increasing the complexity of the encryption scheme. The security performance of the proposed algorithm is analyzed in detail by comparing it with traditional Arnold algorithm, histogram, key space, correlation, information entropy, differential attack, and robustness. The experimental results show that the scheme has good performance and improves the security of image encryption and transmission.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Computer Science, Information Systems
Xia Liang, Jie Guo, Peide Liu
Summary: This paper investigates a novel consensus model based on social networks to manage manipulative and overconfident behaviors in large-scale group decision-making. By proposing a novel clustering model and improved methods, the consensus reaching is effectively facilitated. The feedback mechanism and management approach are employed to handle decision makers' behaviors. Simulation experiments and comparative analysis demonstrate the effectiveness of the model.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Xiang Li, Haiwang Guo, Xinyang Deng, Wen Jiang
Summary: This paper proposes a method based on class gradient networks for generating high-quality adversarial samples. By introducing a high-level class gradient matrix and combining classification loss and perturbation loss, the method demonstrates superiority in the transferability of adversarial samples on targeted attacks.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Lingyun Lu, Bang Wang, Zizhuo Zhang, Shenghao Liu
Summary: Many recommendation algorithms only rely on implicit feedbacks due to privacy concerns. However, the encoding of interaction types is often ignored. This paper proposes a relation-aware neural model that classifies implicit feedbacks by encoding edges, thereby enhancing recommendation performance.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Jaehong Yu, Hyungrok Do
Summary: This study discusses unsupervised anomaly detection using one-class classification, which determines whether a new instance belongs to the target class by constructing a decision boundary. The proposed method uses a proximity-based density description and a regularized reconstruction algorithm to overcome the limitations of existing one-class classification methods. Experimental results demonstrate the superior performance of the proposed algorithm.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Hui Tu, Shifei Ding, Xiao Xu, Haiwei Hou, Chao Li, Ling Ding
Summary: Border-Peeling algorithm is a density-based clustering algorithm, but its complexity and issues on unbalanced datasets restrict its application. This paper proposes a non-iterative border-peeling clustering algorithm, which improves the clustering performance by distinguishing and associating core points and border points.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Long Tang, Pan Zhao, Zhigeng Pan, Xingxing Duan, Panos M. Pardalos
Summary: In this work, a two-stage denoising framework (TSDF) is proposed for zero-shot learning (ZSL) to address the issue of noisy labels. The framework includes a tailored loss function to remove suspected noisy-label instances and a ramp-style loss function to reduce the negative impact of remaining noisy labels. In addition, a dynamic screening strategy (DSS) is developed to efficiently handle the nonconvexity of the ramp-style loss.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Raghunathan Krishankumar, Sundararajan Dhruva, Kattur S. Ravichandran, Samarjit Kar
Summary: Health 4.0 is gaining global attention for better healthcare through digital technologies. This study proposes a new decision-making framework for selecting viable blockchain service providers in the Internet of Medical Things (IoMT). The framework addresses the limitations in previous studies and demonstrates its applicability in the Indian healthcare sector. The results show the top ranking BSPs, the importance of various criteria, and the effectiveness of the developed model.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Tao Tan, Hong Xie, Liang Feng
Summary: This paper proposes a heterogeneous update idea and designs HetUp Q-learning algorithm to enlarge the normalized gap by overestimating the Q-value corresponding to the optimal action and underestimating the Q-value corresponding to the other actions. To address the limitation, a softmax strategy is applied to estimate the optimal action, resulting in HetUpSoft Q-learning and HetUpSoft DQN. Extensive experimental results show significant improvements over SOTA baselines.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Chao Yang, Xianzhi Wang, Lina Yao, Guodong Long, Guandong Xu
Summary: This paper proposes a dynamic transformer-based architecture called Dyformer for multivariate time series classification. Dyformer captures multi-scale features through hierarchical pooling and adaptive learning strategies, and improves model performance by introducing feature-map-wise attention mechanisms and a joint loss function.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Xiguang Li, Baolu Feng, Yunhe Sun, Ammar Hawbani, Saeed Hammod Alsamhi, Liang Zhao
Summary: This paper proposes an enhanced scatter search strategy, using opposition-based learning, to solve the problem of automated test case generation based on path coverage (ATCG-PC). The proposed ESSENT algorithm selects the path with the lowest path entropy among the uncovered paths as the target path and generates new test cases to cover the target path by modifying the dimensions of existing test cases. Experimental results show that the ESSENT algorithm outperforms other state-of-the-art algorithms, achieving maximum path coverage with fewer test cases.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Shirin Dabbaghi Varnosfaderani, Piotr Kasprzak, Aytaj Badirova, Ralph Krimmel, Christof Pohl, Ramin Yahyapour
Summary: Linking digital accounts belonging to the same user is crucial for security, user satisfaction, and next-generation service development. However, research on account linkage is mainly focused on social networks, and there is a lack of studies in other domains. To address this, we propose SmartSSO, a framework that automates the account linkage process by analyzing user routines and behavior during login processes. Our experiments on a large dataset show that SmartSSO achieves over 98% accuracy in hit-precision.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Renchao Wu, Jianjun He, Xin Li, Zuguo Chen
Summary: This paper proposes a memetic algorithm with fuzzy-based population control (MA-FPC) to solve the joint order batching and picker routing problem (JOBPRP). The algorithm incorporates batch exchange crossover and a two-level local improvement procedure. Experimental results show that MA-FPC outperforms existing algorithms in terms of solution quality.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Guoxiang Zhong, Fagui Liu, Jun Jiang, Bin Wang, C. L. Philip Chen
Summary: In this study, we propose the AMFormer framework to address the problem of mixed normal and anomaly samples in deep unsupervised time-series anomaly detection. By refining the one-class representation and introducing the masked operation mechanism and cost sensitive learning theory, our approach significantly improves anomaly detection performance.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Jin Zhou, Kang Zhou, Gexiang Zhang, Ferrante Neri, Wangyang Shen, Weiping Jin
Summary: In this paper, the authors focus on the issue of multi-objective optimisation problems with redundant variables and indefinite objective functions (MOPRVIF) in practical problem-solving. They propose a dual data-driven method for solving this problem, which consists of eliminating redundant variables, constructing objective functions, selecting evolution operators, and using a multi-objective evolutionary algorithm. The experiments conducted on two different problem domains demonstrate the effectiveness, practicality, and scalability of the proposed method.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Georgios Charizanos, Haydar Demirhan, Duygu Icen
Summary: This article proposes a new fuzzy logistic regression framework that addresses the problems of separation and imbalance while maintaining the interpretability of classical logistic regression. By fuzzifying binary variables and classifying subjects based on a fuzzy threshold, the framework demonstrates superior performance on imbalanced datasets.
INFORMATION SCIENCES
(2024)