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A Review of Intelligent Configuration and Its Security for Complex Networks

Chinese Journal of Electronics 2024年第4期33卷 920-947页

作者： Yue ZHAO Bin YANG Fei TENG Xianhua NIU Ning HU Bo TIAN Science and Technology on Communication Security Laboratory School of Computer and Information Engineering Chuzhou University School of Computing and Artificial Intelligence Southwest Jiaotong University School of Computer and Software Engineering Xihua University Cyberspace Institute of Advanced Technology Guangzhou University

Complex networks are becoming more complex because of the use of many components with diverse technologies. In fact, manual configuration that makes each component interoperable has breed latent danger to system security. There is still no comprehensive review of these studies and prospects for further research. According to the complexity of component configuration and difficulty of security assurance in typical complex networks, this paper systematically reviews the abstract models and formal analysis methods required for intelligent configuration of complex networks, specifically analyzes, and compares the current key technologies such as configuration semantic awareness, automatic generation of security configuration, dynamic deployment, and verification evaluation. These technologies can effectively improve the security of complex networks intelligent configuration and reduce the complexity of operation and maintenance. This paper also summarizes the mainstream construction methods of complex networks configuration and its security test environment and detection index system, which lays a theoretical foundation for the formation of the comprehensive effectiveness verification capability of configuration security. The whole lifecycle management system of configuration security process proposed in this paper provides an important technical reference for reducing the complexity of network operation and maintenance and improving network security.

关键词： Complex networks Intelligent configuration Configuration security Software defined network Lifecycle management

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A Pre-Selection-Based Ant Colony System for Integrated Resources Scheduling Problem at Marine Container Terminal

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computers, Materials & Continua 2024年第8期80卷 2363-2385页

作者： Rong Wang Xinxin Xu Zijia Wang Fei Ji Nankun Mu School of Electronic and Information Engineering South China University of TechnologyGuangzhou510641China School of Computer Science and Technology Ocean University of ChinaQingdao266100China School of Computer Science and Cyber Engineering Guangzhou UniversityGuangzhou510006China School of Computer Science Chongqing UniversityChongqing400044China

Marine container terminal(MCT)plays a key role in the marine intelligent transportation system and international logistics ***,the efficiency of resource scheduling significantly influences the operation performance of *** solve the practical resource scheduling problem(RSP)in MCT efficiently,this paper has contributions to both the problem model and the algorithm ***,in the problem model,different from most of the existing studies that only consider scheduling part of the resources in MCT,we propose a unified mathematical model for formulating an integrated *** new integrated RSP model allocates and schedules multiple MCT resources simultaneously by taking the total cost minimization as the ***,in the algorithm design,a pre-selection-based ant colony system(PACS)approach is proposed based on graphic structure solution representation and a pre-selection *** the one hand,as the RSP can be formulated as the shortest path problem on the directed complete graph,the graphic structure is proposed to represent the solution encoding to consider multiple constraints and multiple factors of the RSP,which effectively avoids the generation of infeasible *** the other hand,the pre-selection strategy aims to reduce the computational burden of PACS and to fast obtain a higher-quality *** evaluate the performance of the proposed novel PACS in solving the new integrated RSP model,a set of test cases with different sizes is *** results and comparisons show the effectiveness and efficiency of the PACS algorithm,which can significantly outperform other state-of-the-art algorithms.

关键词： Resource scheduling problem(RSP) ant colony system(ACS) marine container terminal(MCT) pre-selection strategy

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A New Prediction System Based on Self-Growth Belief Rule Base with Interpretability Constraints

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computers, Materials & Continua 2023年第5期75卷 3761-3780页

作者： Yingmei Li Peng Han Wei He Guangling Zhang Hongwei Wei Boying Zhao School of Computer Science and Information Engineering Harbin Normal UniversityHarbin150025China

Prediction systems are an important aspect of intelligent *** engineering practice,the complex system structure and the external environment cause many uncertain factors in the model,which influence the modeling accuracy of the *** belief rule base(BRB)can implement nonlinear modeling and express a variety of uncertain information,including fuzziness,ignorance,randomness,***,the BRB system also has two main problems:Firstly,modeling methods based on expert knowledge make it difficult to guarantee the model’s ***,interpretability is not considered in the optimization process of current research,resulting in the destruction of the interpretability of *** balance the accuracy and interpretability of the model,a self-growth belief rule basewith interpretability constraints(SBRB-I)is *** reasoning process of the SBRB-I model is based on the evidence reasoning(ER)***,the self-growth learning strategy ensures effective cooperation between the datadriven model and the expert system.A case study showed that the accuracy and interpretability of the model could be *** SBRB-I model has good application prospects in prediction systems.

关键词： Belief rule base evidence reasoning interpretability optimization prediction system

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FIMKD: Feature-Implicit Mapping Knowledge Distillation for RGB-D Indoor Scene Semantic Segmentation

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第12期5卷 6488-6499页

作者： Zhou, Wujie Xiao, Yuxiang Liu, Yuanyuan Jiang, Qiuping Zhejiang University of Science & Technology School of Information & Electronic Engineering Hangzhou310023 China Nanyang Technological University School of Computer Science and Engineering Singapore308232 Singapore China University of Geosciences School of Computer and Technology Wuhan430074 China Ningbo University School of Information Science and Engineering Ningbo315211 China

Depth images are often used to improve the geometric understanding of scenes owing to their intuitive distance properties. Although there have been significant advancements in semantic segmentation tasks using red-green-blue-depth (RGB-D) images, the complexity of existing methods remains high. Furthermore, the requirement for high-quality depth images increases the model inference time, which limits the practicality of these methods. To address this issue, we propose a feature-implicit mapping knowledge distillation (FIMKD) method and a cross-modal knowledge distillation (KD) architecture to leverage deep modal information for training and reduce the model dependence on this information during inference. The approach comprises two networks: FIMKD-T, a teacher network that uses RGB-D data, and FIMKD-S, a student network that uses only RGB data. FIMKD-T extracts high-frequency information using the depth modality and compensates for the loss of RGB details due to a reduction in resolution during feature extraction by the high-frequency feature enhancement module, thereby enhancing the geometric perception of semantic features. In contrast, the FIMKD-S network does not employ deep learning techniques;instead, it uses a nonlearning approach to extract high-frequency information. To enable the FIMKD-S network to learn deep features, we propose a feature-implicit mapping KD for feature distillation. This mapping technique maps the features in channel and space to a low-dimensional hidden layer, which helps to avoid inefficient single-pattern student learning. We evaluated the proposed FIMKD-S∗ (FIMKD-S with KD) on the NYUv2 and SUN-RGBD datasets. The results demonstrate that both FIMKD-T and FIMKD-S∗ achieve state-of-the-art performance. Furthermore, FIMKD-S∗ provides the best performance balance. © 2020 IEEE.

关键词： Semantic Segmentation

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Mitigation of Optical Multipath Interference Algorithms in IM-DD Transmission System

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China Communications 2024年第4期21卷 1-9页

作者： Huo Jiahao Zhu Jin Zhu Zuqing Zhang Xiaoying Liu Shaonan Tao Jianlong Wei Huangfu School of Computer and Communication Engineering University of Science and Technology BeijingBeijing 100083China School of Information Science and Technology University of Science and Technology of ChinaHefei 230026China

This paper aimed to propose two algorithms,DA-M and RF-M,of reducing the impact of multipath interference(MPI)on intensity modulation direct detection(IM-DD)systems,particularly for four-level pulse amplitude modulation(PAM4)***-M reduced the fluctuation by averaging the signal in blocks,RF-M estimated MPI by subtracting the decision value of the corresponding block from the mean value of a signal block,and then generated interference-reduced samples by subtracting the interference signal from the product of the corresponding MPI estimate and then weighting *** paper firstly proposed to separate the signal before decision-making into multiple blocks,which significantly reduced the complexity of DA-M and *** results showed that the MPI noise of 28 GBaud IMDD system under the linewidths of 1e5 Hz,1e6 Hz and 10e6 Hz can be effectively alleviated.

关键词： IM-DD multipath interference PAM4

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Early Detection of Colletotrichum Kahawae Disease in Coffee Cherry Based on computer Vision Techniques

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computer Modeling in engineering & sciences 2024年第4期139卷 759-782页

作者： Raveena Selvanarayanan Surendran Rajendran Youseef Alotaibi Department of Computer Science and Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical ScienceChennai602105India Department of Computer Science College of Computer and Information SystemsUmm Al-Qura UniversityMakkah21955Saudi Arabia

Colletotrichum kahawae(Coffee Berry Disease)spreads through spores that can be carried by wind,rain,and insects affecting coffee plantations,and causes 80%yield losses and poor-quality coffee *** deadly disease is hard to control because wind,rain,and insects carry *** researchers utilized a deep learning system to identify CBD in coffee cherries at three growth stages and classify photographs of infected and uninfected cherries with 93%accuracy using a random forest *** the dataset is too small and noisy,the algorithm may not learn data patterns and generate accurate *** overcome the existing challenge,early detection of Colletotrichum Kahawae disease in coffee cherries requires automated processes,prompt recognition,and accurate *** proposed methodology selects CBD image datasets through four different stages for training and *** to train a model on datasets of coffee berries,with each image labeled as healthy or *** themodel is trained,SHAP algorithmto figure out which features were essential formaking predictions with the proposed *** of these characteristics were the cherry’s colour,whether it had spots or other damage,and how big the Lesions *** inception is important for classification to virtualize the relationship between the colour of the berry is correlated with the presence of *** evaluate themodel’s performance andmitigate excess fitting,a 10-fold cross-validation approach is *** involves partitioning the dataset into ten subsets,training the model on each subset,and evaluating its *** comparison to other contemporary methodologies,the model put forth achieved an accuracy of 98.56%.

关键词： computer vision coffee berry disease colletotrichum kahawae XG boost shapley additive explanations

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A Review on Smart Healthcare employing Quantum Internet of Things

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IEEE engineering Management Review 2024年 1-9页

作者： Sutradhar, Kartick Venkatesh, Ranjitha Venkatesh, Priyanka Department of Computer Science and Engineering Indian Institute of Information Technology Sri City India Department of Computer Science and Engineering GITAM School of Technology Bengaluru India Department of Computer Science and Engineering Presidency University Bengaluru India

The Quantum Internet of Things (QIoT) in the healthcare industry holds the promise of transforming patient care, diagnostics, and medical research. Quantum-enhanced sensors, communication, and computation offer unprecedented capabilities that can revolutionize how healthcare services are delivered and experienced. This paper explores the potential of QIoT in the context of smart healthcare, where interconnected quantum-enabled devices and systems create an ecosystem that enhances data security, enables real-time monitoring, and advances medical knowledge. We delve into the applications of quantum sensors in precise health monitoring, the role of quantum communication in secure telemedicine, and the computational power of quantum computing in drug discovery and personalized medicine. We discuss challenges such as technical feasibility, scalability, and regulatory considerations, along with the emerging trends and opportunities in this transformative field. By examining the intersection of quantum technologies and smart healthcare, this paper aims to shed light on the novel approaches and breakthroughs that could redefine the future of healthcare delivery and patient outcomes. IEEE

关键词： Internet of things

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FGM-SPCL:Open-Set Recognition Network for Medical Images Based on Fine-Grained Data Mixture and Spatial Position Constraint Loss

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Chinese Journal of Electronics 2024年第4期33卷 1023-1033页

作者： Ruru ZHANG Haihong E Lifei YUAN Yanhui WANG Lifei WANG Meina SONG School of Computer Science Beijing University of Posts and Telecommunications Engineering Research Center of Information Networks Ministry of Education Hebei Eye Hospital

The current intelligent auxiliary diagnosis models all follow the closed-set recognition setting. After the model is deployed online, the input data is often not completely controlled. Diagnosing an untrained disease as a known category would lead to serious medical malpractice. Therefore, realizing the open-set recognition is significant to the safe operation of the intelligent auxiliary diagnosis model. Currently, most open-set recognition models are studied for natural images, and it is very challenging to obtain clear and concise decision boundaries between known and unknown classes when applied to fine-grained medical images. We propose an open-set recognition network for medical images based on fine-grained data mixture and spatial position constraint loss(FGM-SPCL) in this *** the fine graininess of medical images and the diversity of unknown samples, we propose a fine-grained data mixture(FGM) method to simulate unknown data by performing a mixing operation on known data to expand the coverage of unknown data difficulty levels. In order to obtain a concise and clear decision boundary, we propose a spatial position constraint loss(SPCL) to control the position distribution of prototypes and samples in the feature space and maximize the distance between known classes and unknown classes. We validate on a private ophthalmic OCT dataset, and extensive experiments and analyses demonstrate that FGM-SPCL outperforms state-of-the-art models.

关键词： Analytical models Fine-grained image recognition Prototypes Aerospace electronics Spatial databases Robustness Data models

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UAV-Assisted Multi-Object Computing Offloading for Blockchain-Enabled Vehicle-to-Everything Systems

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computers, Materials & Continua 2024年第12期81卷 3927-3950页

作者： Ting Chen Shujiao Wang Xin Fan Xiujuan Zhang Chuanwen Luo Yi Hong School of Computer Science and Engineering University of Electronic Science and Technology of ChinaChengdu611731China School of Computer Science Qufu Normal UniversityRizhao276826China School of Information Science and Technology Beijing Forestry UniversityBeijing100083China

This paper investigates an unmanned aerial vehicle(UAV)-assisted multi-object offloading scheme for blockchain-enabled Vehicle-to-Everything(V2X)*** to the presence of an eavesdropper(Eve),the system’s com-munication links may be *** paper proposes deploying an intelligent reflecting surface(IRS)on the UAV to enhance the communication performance of mobile vehicles,improve system flexibility,and alleviate eavesdropping on communication *** links for uploading task data from vehicles to a base station(BS)are protected by IRS-assisted physical layer security(PLS).Upon receiving task data,the computing resources provided by the edge computing servers(MEC)are allocated to vehicles for task *** blockchain-based computation offloading schemes typically focus on improving network performance,such as minimizing energy consumption or latency,while neglecting the Gas fees for computation offloading and the costs required for MEC computation,leading to an imbalance between service fees and resource *** paper uses a utility-oriented computation offloading scheme to balance costs and *** paper proposes alternating phase optimization and power optimization to optimize the energy consumption,latency,and communication secrecy rate,thereby maximizing the weighted total utility of the *** results demonstrate a notable enhancement in the weighted total system utility and resource utilization,thereby corroborating the viability of our approach for practical applications.

关键词： UAV intelligent reflecting surface vehicle to everything task offloading phase shift optimization

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Secure Transmission Scheme for Blocks in Blockchain-Based Unmanned Aerial Vehicle Communication Systems

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computers, Materials & Continua 2024年第11期81卷 2195-2217页

作者： Ting Chen Shuna Jiang Xin Fan Jianchuan Xia Xiujuan Zhang Chuanwen Luo Yi Hong School of Computer Science and Engineering University of Electronic Science and Technology of ChinaChengdu611731China School of Computer Science Qufu Normal UniversityRizhao276826China School of Information Science and Technology Beijing Forestry UniversityBeijing100083China

In blockchain-based unmanned aerial vehicle(UAV)communication systems,the length of a block affects the performance of the *** transmission performance of blocks in the form of finite character segments is also affected by the block ***,it is crucial to balance the transmission performance and blockchain performance of blockchain communication systems,especially in wireless environments involving *** paper investigates a secure transmission scheme for blocks in blockchain-based UAV communication systems to prevent the information contained in blocks from being completely eavesdropped during *** our scheme,using a friendly jamming UAV to emit jamming signals diminishes the quality of the eavesdropping channel,thus enhancing the communication security performance of the source *** the constraints of maneuverability and transmission power of the UAV,the joint design of UAV trajectories,transmission power,and block length are proposed to maximize the average minimum secrecy rate(AMSR).Since the optimization problem is non-convex and difficult to solve directly,we first decompose the optimization problem into subproblems of trajectory optimization,transmission power optimization,and block length ***,based on firstorder approximation techniques,these subproblems are reformulated as convex optimization ***,we utilize an alternating iteration algorithm based on the successive convex approximation(SCA)technique to solve these subproblems *** simulation results demonstrate that our proposed scheme can achieve secure transmission for blocks while maintaining the performance of the blockchain.

关键词： Unmanned aerial vehicles blockchain finite blocklength block transmission alternating optimization

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