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2024 7th International Conference on Computer Information science and Artificial Intelligence, CISAI 2024

作者： Wu, Jiawei Liang, Shuaishuai Feng, Huibin College of Computer and Data Science Fuzhou University Fujian Fuzhou China School of Computer and Big Data Minjiang University Fujian Fuzhou China

ISBN: (纸本)9798400707254

The development of the aerospace technology enables countries around the world to launch a large number of satellites to carry out extraterrestrial missions. This also poses greater challenges to the control of satellites. The extremely long communication time between satellites and the ground has led to the necessity of autonomous onboard control capability for satellites. The rise of reinforcement learning (RL) technology has driven research on applying RL technology to satellite control problems. This paper attempts to apply the Distributed Soft Actor Critic with Three Improvements (DSAC-T) algorithm to the adaptive continuous control problem of satellite attitude. The problem is described as a reinforcement learning model that controls the satellite to perform a large-angle slew maneuvers and maintain a desired orientation. By setting up rotation experiments, the results show that the DSAC-T algorithm can control satellite to perform rotation tasks more quickly and smoothly than existing continuous control algorithms. © 2024 Copyright held by the owner/author(s).

关键词： Reinforcement learning

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Secure and Lightweight Signcryption Scheme With Group Equality Test for Heterogeneous WBAN

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IEEE Internet of Things Journal 2025年第13期12卷 25314-25332页

作者： Zhang, Qijia Zhang, Jianhong Yang, Nan Tian, Youliang Guizhou University State Key Laboratory of Public Big Data College of Computer Science and Technology Guiyang050025 China North China University of Technology College of Information Sciences and Technology Beiing100144 China

Wireless body area network (WBAN) integrates body sensors to collect and upload various health indicators, which facilitates timely remote healthcare. To realize the real-time monitoring of the patient’s health status while ensuring the security of sensitive data, signcryption schemes with equality test provide a feasible solution. Nevertheless, most of the existing schemes suffer from heavy computational burdens and are vulnerable to some inherent threats, such as offline message recovery attack and known session temporary key attack. Additionally, some of them cannot provide the essential security properties. To cope with these problems, this paper constructs a secure and lightweight signcryption scheme with group equality test, which is suitable for the heterogeneous environment. To formally define the resistance to offline message recovery attack and known session temporary key attack, we first propose two corresponding security models. Then, we introduce a group mechanism to the equality test to support the aforementioned security properties. Besides, we adopt the online/offline construction to avert the time-consuming operations in the real-time data processing phase. Furthermore, our scheme supports message aggregation to reduce the computational overhead of handling multiple messages. Formal security proof shows that our scheme satisfies confidentiality and unforgeability. Compared to several recent schemes, the experimental results demonstrate that our scheme enjoys the best performance in terms of both computational overhead and communication cost. With implementation, our scheme is proved to be feasible for lightweight devices in real-world applications. © 2014 IEEE.

关键词： Electronic health record

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Zero-inflated non-central negative binomial distribution

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Applied Mathematics(A Journal of Chinese Universities) 2022年第2期37卷 187-198页

作者： TIAN Wei-zhong LIU Ting-ting YANG Yao-ting College of Big Data and Internet Shenzhen Technology UniversityShenzhen 518118China School of Science Xi'an University of TechnologyXi'an 710054China

In this article, the zero-inflated non-central negative binomial(ZINNB) distribution is introduced. Some of its basic properties are obtained. In addition, we use the maximum likelihood estimation method to estimate t... 详细信息

关键词： zero-in ated non-central negative binomial distribution maximum likelihood estimation good-ness of fit

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Enhancing cuckoo search algorithm with complement strategy

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International Journal of Innovative Computing and Applications 2022年第5-6期13卷 314-324页

作者： Peng, Hu Lu, Hua Deng, Changshou School of Computer and Big Data Science Jiujiang University Jiujiang332005 China

Cuckoo search (CS) algorithm is proposed by Yang and Deb, which is a simple and effective swarm intelligence algorithm. In each iteration, the CS search for new solutions by the global explorative random walk and the local random walk, the greedy strategy is used to choose a better solution. However, the CS uses a single strategy and fixed parameters, in which performance of the CS in balancing exploitation and exploration is inadequate, which results in poor convergence performance of the CS. To cope with this problem, a novel CS variant with complement strategy (CoCS) was proposed by us, in which the new solution is generated by two strategies in a random manner. One of the strategy is an improved Lêvy flights, and the other is adaptive to determine the step size according to the fitness value of the step size and the number of current iterations. The algorithm also uses an improved random walk. The proposed CoCS, the standard CS, and other excellent CS variants were tested on 28 benchmark functions of CEC 2013 test suite. Experimental results prove that the CoCS is superior to these competitors. Copyright © 2022 Inderscience Enterprises Ltd.

关键词： Global optimization

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Adaptive Wavelet Convolution Stochastic Analysis Graph Neural Network for Remaining Useful Life Prediction

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IEEE Sensors Journal 2025年第11期25卷 19428-19441页

作者： Hu, Qidi Su, Binyi Kong, Jinzhen Liu, Weipeng Hebei University of Technology School of Artificial Intelligence and Data Science Tianjin300130 China Hebei University of Technology School of Mechanical Engineering Tianjin300130 China

The prediction of the Remaining Useful Life (RUL) of stochastically degrading devices is of critical importance for Prognostics and Health Management (PHM). However, most of the existing approaches overlook the inherent coupling of trends and fluctuations in the degradation process. Meanwhile, these methods are struggling to effectively model the random fluctuations component in the degradation process and may lead to inaccurate prediction. To address these limitations, we propose a modified RUL prediction framework WTSAGNN. The framework extends the spatiotemporal dependencies of multi-sensor signals into the frequency domain. By leveraging the proposed adaptive orthogonal wavelet convolution to more effectively decouple the trend and fluctuation components of the degradation process. Furthermore, we introduce a stochastic differential network (SDN) to replace the traditional multilayer perceptron (MLP). The proposed method enhances the robustness of neural networks against stochastic variations in degradation processes through explicit stochastic modeling. Experimental results demonstrate that WTSAGNN outperforms existing state-of-the-art(SOTA) methods on benchmark datasets, achieving up to a 9.1% improvement in prediction accuracy with only a limited increase in computational overhead. In addition, the proposed modules are plug-and-play, allowing seamless integration with existing data-driven prediction frameworks. © 2025 IEEE.

关键词： Graph neural networks

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Homomorphic Encryption-Based Privacy Protection data Processing Strategies in Fog Computing 2

Homomorphic Encryption-Based Privacy Protection Data Process...

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2nd International Conference on big data and Privacy Computing, BDPC 2024

作者： Song, Shiyang Tang, Jinhai Wang, Haozhe Yuan, Dongxu Zhang, Zhiyuan Alibaba Cloud Big Data Application College Zhuhai College of Science and Technology Zhuhai China

ISBN: (纸本)9798350307597

With the development of Intelligent Transportation Systems (ITS), real-time processing and privacy protection for traffic data become particularly important. In this research, we explore how to process traffic data efficiently and securely in fog computing environments, especially in wireless in-vehicle networks. First, we propose a homomorphic encryption-based strategy that performs computation on ciphertexts, eliminating the need for frequent decryption and thus achieving higher data processing efficiency. Then, we provide an in-depth discussion on data integrity and real-time performance, and propose a novel data validation method to ensure data integrity and real-time updates in fog computing environments. In addition, we designed a series of simulation experiments using virtual data to verify the effectiveness of our approach. The experimental results show that our strategy not only greatly improves the data processing speed, but also effectively guarantees the privacy and integrity of the data. Overall, this study provides a new and efficient method for traffic data processing in fog computing environments, which is an important reference value for future traffic data processing. © 2024 IEEE.

关键词： Differential privacy

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CoMO-NAS: Core-Structures-Guided Multi-Objective Neural Architecture Search for Multi-Modal Classification 24

CoMO-NAS: Core-Structures-Guided Multi-Objective Neural Arch...

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32nd ACM International Conference on Multimedia, MM 2024

作者： Fu, Pinhan Liang, Xinyan Qian, Yuhua Guo, Qian Wei, Zhifang Li, Wen Institute of Big Data Science and Industry Shanxi University Taiyuan China School of Computer Science and Technology Taiyuan University of Science and Technolog Taiyuan China

ISBN: (纸本)9798400706868

Most existing NAS-based multi-modal classification (MMC-NAS) methods are optimized using the classification *** can not simultaneously provide multiple models with diverse perferences such as model complex and classification performance for meeting different users' demands. Combining NAS-MMC with multi-objective optimization is a nature way for this issue. However, the challenge problem of this solution is the high computation cost. For multi-objective optimization, the computing bottleneck is pareto front search. Some higher-quality MMC models (namely core structures, CSs) consisting of high-quality features and fusion operators are easier to identify. We find that CSs have a close relation with the pareto front (PF), i.e., the individuals lying in PF contain the CSs. Based on the finding, we propose an efficient multi-objective neural architecture search for multi-modal classification by applying CSs to guide the PF search (CoMO-NAS). In conclusion, experimental results thoroughly demonstrate the effectiveness of our CoMO-NAS. Compared to state-of-the-art competitors on benchmark multi-modal tasks, we achieve comparable performance with lower model complexity in shorter search time. © 2024 ACM.

关键词： Multiobjective optimization

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Research on a technology of Mail Anti-virus Gateway for Industrial Internet

Research on a Technology of Mail Anti-virus Gateway for Indu...

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2023 IEEE International Conference on Image Processing and Computer Applications, ICIPCA 2023

作者： Wu, Yuhong Lv, Yunshan Zhang, Ling School of Big Data & Computer Science Engineering Chongqing College of Mobile Communication Key Laboratory of Public Big Data Security Technology Chongqing China School of Computer Science and Technology Chongqing University of Posts and Telecommunications Chongqing China

ISBN: (纸本)9798350314670

With the rapid rise of the Industrial Internet, emails that convey a large amount of information require a strong network security environment. Aiming at the increasingly complex mail virus prevention and control work under the background of the industrial Internet, this paper designs and implements a mail anti-virus gateway system. First, design the overall process and structure of the mail virus processing system;then, design an extended mail receiving and sending protocol on the basis of the public framework, thereby ensuring the convenience of the system for use in different roles and environments. In the detection and filtering part of mail virus, an anti-virus engine containing multiple sub-function modules is designed to detect and filter viruses in mail text and attachments. Through the function test of 1000 kinds of virus mails, it is found that the mail anti-virus gateway system designed in this article can detect and filter most types of mail viruses. Compared with the virus detection on the client and server, the anti-virus gateway system has better performance And efficiency. © 2023 IEEE.

关键词： Network security

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Visual abstraction of dynamic network via improved multi-class blue noise sampling

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Frontiers of Computer science 2023年第1期17卷 171-185页

作者： Yanni PENG Xiaoping FAN Rong CHEN Ziyao YU Shi LIU Yunpeng CHEN Ying ZHAO Fangfang ZHOU School of Computer Science and Engineering Central South UniversityChangsha 410083China Institute of Big Data Hunan University of Finance and EconomicsChangsha 410205China Rail Data Research and Application Key Laboratory of Hunan Province Changsha 410083China

Massive sequence view (MSV) is a classic timeline-based dynamic network visualization approach. However, it is vulnerable to visual clutter caused by overlapping edges, thereby leading to unexpected misunderstanding of time-varying trends of network communications. This study presents a new edge sampling algorithm called edge-based multi-class blue noise (E-MCBN) to reduce visual clutter in MSV. Our main idea is inspired by the multi-class blue noise (MCBN) sampling algorithm, commonly used in multi-class scatterplot decluttering. First, we take a node pair as an edge class, which can be regarded as an analogy to classes in multi-class scatterplots. Second, we propose two indicators, namely, class overlap and inter-class conflict degrees, to measure the overlapping degree and mutual exclusion, respectively, between edge classes. These indicators help construct the foundation of migrating the MCBN sampling from multi-class scatterplots to dynamic network samplings. Finally, we propose three strategies to accelerate MCBN sampling and a partitioning strategy to preserve local high-density edges in the MSV. The result shows that our approach can effectively reduce visual clutters and improve the readability of MSV. Moreover, our approach can also overcome the disadvantages of the MCBN sampling (i.e., long-running and failure to preserve local high-density communication areas in MSV). This study is the first that introduces MCBN sampling into a dynamic network sampling.

关键词： dynamic network visualization massive sequence view multi-class blue noise sampling visual abstraction

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A Novel Dynamic Practical Byzantine Fault Tolerance Protocol Based on Node Grouping 24

A Novel Dynamic Practical Byzantine Fault Tolerance Protocol...

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12th International Conference on Communications and Broadband Networking, ICCBN 2024

作者： Tan, Bingbing Chen, Yanli Zhou, Yonghui Dong, Zhicheng School of Big Data and Computer Science Guizhou Normal University China Tibet Univerity China

ISBN: (纸本)9798400717109

The Practical Byzantine Fault Tolerance protocol (PBFT) has been widely deployed in the blockchain network. However, two main issues, the communication complexity and the inability of nodes to join/exit the network without restarting the system, significantly degrade consensus efficiency. A novel dynamic practical byzantine fault tolerance protocol based on node grouping (NG-PBFT) is proposed as a solution to these problems. This protocol is realized through the grouping of nodes into consensus and observation groups. The nodes in observation group preprocess nodes' joining/exiting requests, while the nodes in consensus group reach consensus about the preprocessed results. Furthermore, an adaptive three phases or two phases consensus mechanism that can effectively improve consensus efficiency is proposed. We provide theoretical complexity to show that our protocol reduces the communication complexity of consensus and improves consensus efficiency significantly. © 2024 ACM.

关键词： Authentication Protocol

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