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3rd IEEE International Conference on Civil Aviation Safety and information Technology, ICCASIT 2021

作者： Shaoxi, Liu Jun, Shen Jie, Ren Ying, Huang Southeast University Key Laboratory of Computer Network & Information Integration of Ministry of Education Nanjing China AVIC Chengdu Aircraft Design and Research Institute Chengdu China Nanjing Origin Information Technology Co. Ltd Nanjing China

ISBN: (纸本)9781665425186

In some new network architectures, in order to improve the scalability of services, scholars in recent years have been trying their best to explore the strategy of combining several small-grained services into large-grained services that can respond to user needs. In response to this problem, this paper studies and analyzes the relationship between services, and proposes a service relationship model based on fragmented logic. The model defines the service relationship structure and its related relationship operations. Then the model is applied in the SDEN network to complete the system requirements of service dynamic combination, thereby verifying that the model can improve the flexibility and scalability of the actual application system. © 2021 IEEE

关键词： Scalability

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A Scientific Workflow Engine Design and Implementation

A Scientific Workflow Engine Design and Implementation

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第四届公共管理与智能社会国际学术会议

作者： Zhichao Zhang Meng Guo Tingting Guo Key Laboratory of' Computing Power Network and Information Security of Ministry of Education Shandong Computer Science Center (National Supercomputing Center in Jinan) Qilu University of Technology (Shandong Academy of Sciences) Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Inspur General Software Co.Ltd. Shandong Carbon Manager Group Co.Ltd.

This paper designs and implements a scientific workflow engine that follows the BPMN 2.0, enriching existing research on scientific workflow engine specification and theory. The engine is implemented using the Java language and adopts a layered architecture, including a process virtual machine, a BPMN model engine and a scientific workflow model engine from the bottom up, which has good scalability and is able to provide powerful support for the design and operation of scientific workflows so as to process scientific research data more efficiently.

关键词： Scientific workflow workflow workflow engine BPMN 2.0

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Detection method of trusted blockchain link flood attack based on trusted execution environment

Detection method of trusted blockchain link flood attack bas...

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information Technology: IoT and Smart City (ITIoTSC), International Conference on

作者： Ruixue Kuang Lianhai Wang Shuhui Zhang Shujiang Xu Wei Shao Qizheng Wang Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center (National Supercomputer Center in Jinan) Qilu University of Technology (Shandong Academy of Sciences) Jinan Shandong China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan Shandong China

ISBN: (数字)9798350328349

ISBN: (纸本)9798350328356

In order to improve the detection accuracy and improve the detection speed, this paper designs a detection method of trusted blockchain link flood attack based on the trusted execution environment. First, above all, analyze the trusted block chain structure, then design the trusted block chain link flood attack detection algorithm, and finally the trusted execution environment is used to realize the trusted block chain link flood attack detection. The experimental results prove that the false alarm rate and leakage detection rate of the detection method of the flood flood attack designed based on the trusted execution environment are both low, with the lowest value only 3% and 0.98%. The detection accuracy is high, the detection time is short, and the detection can be completed in at least 13s. It can be proved that the performance of this design method is better and has certain application value.

关键词： Accuracy information resources Smart cities computer hacking Design methodology Blockchains Floods

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Proceedings Research on the Path of High-Quality Development of Big Data Industry in Shandong Province

Proceedings Research on the Path of High-Quality Development...

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作者： Yu Wang Mingle Zhou Chunjing Wang Xingheng Mei Yumei Li Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center (National Supercomputer Center in Jinan) Qilu University of Technology (Shandong Academy of Sciences) Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Qilu University of Technology (Shandong Academy of Sciences)

The big data industry is a major opportunity to promote the development of the digital economy. This paper analyzes the status quo and problems of the big data industry in Shandong Province, combines the connotation of the big data industry chain,and puts forward countermeasure suggestions for the high-quality development of the big data industry in Shandong Province in four aspects, namely, infrastructure construction,data factor market cultivation, and data application development.

关键词： Big data industry Shandong province Big data industry chain High-quality development

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Deep Iterative Reconstruction Network Based on Residual Constraint for Low-Dose CT Imaging

Deep Iterative Reconstruction Network Based on Residual Cons...

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International Conference on Systems and Informatics (ICSAI)

作者： Jin Liu Yanqin Kang Tao Liu TingYu Zhang Yikun Zhang School of Computer and Information Anhui Polytechnic University Wuhu China Key Laboratory of Computer Network and Information Integration (Southeast University) Ministry of Education Nanjing China School of Computer Science and Engineering Southeast University Nanjing China

ISBN: (纸本)9781665474498

clinical low X-ray dose computed tomography (LDCT) scanner often induce high intensity strip artifact and spot nosie, compromising diagnoses and intervention plans. Recently, sparsely constrained and network learning-based frameworks have been shown to be efficient in mitigating such issue. In this work, we propose a deep iterative reconstruction network (DIRNet) model with a residual constraint to synergize the advantages of feature learning and image reconstruction to address the LDCT imaging problem. DIR-Net compose by few iteration units, and all iteration units include three different network modules: projection restoration, residual constraint and image update block. DIR-Net is a promising approach for building an end-to-reconstruction mapping strategy and directly obtaining high-quality CT images. Furthermore, LISTA is used to conFigure the network, and the whole network architecture yields improved interpretability. Qualitative and quantitative analysis in test data shown the promising imaging effects of DIR-Net in quantum noise reduction, block artifact removal and tissue detail texture mantian.

关键词： Strips Statistical analysis Sonogram Computed tomography Imaging Network architecture Image restoration

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Practical Volume-Hiding Encrypted Multi-Maps with Optimal Overhead and Beyond 22

Practical Volume-Hiding Encrypted Multi-Maps with Optimal Ov...

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28th ACM SIGSAC Conference on computer and Communications Security, CCS 2022

作者： Wang, Jianfeng Sun, Shi-Feng Li, Tianci Qi, Saiyu Chen, Xiaofeng School of Cyber Engineering Xidian University China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University China School of Computer Science and Technology Xi'an Jiao Tong University China State Key Laboratory of Integrated Service Networks Xidian University China

ISBN: (纸本)9781450394505

Encrypted multi-map (EMM), as a special case of structured encryption, has attracted extensive attention recently. However, most of EMM constructions reveal the real volumes of queried keys, which can be leveraged to launch leakage-abuse attacks, as demonstrated by Kellaris et al. in CCS 2016 and Kornaropoulos et al. in S&P 2021. In this paper, we propose a practical non-lossy volume-hiding EMM scheme, XorMM, that can achieve optimal query communication complexity with minimal storage cost. Specifically, compared to the state-of-the-art dprfMM (Patel et al. CCS 2019), the client in our scheme receives only ĝ.,"matching results while not suffering from data loss, where ĝ.,"is the maximum volume of all keys. In addition, the storage cost of XorMM is approximately 1.23n, where n is the total number of key/value pairs. In contrast, the query communication and storage complexity of dprfMM is 2ĝ.,"and 2(1+α)n respectively, where 0 © 2022 ACM.

关键词： Data privacy

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A Note on "Constructing Bent Functions Outside the Maiorana-McFarland Class Using a General Form of Rothaus"

arXiv

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arXiv 2025年

作者： Guo, Fei Wang, Zilong Gong, Guang State Key Laboratory of Mathematical Engineering and Advanced Computing Information Engineering University Zhengzhou450001 China State Key Laboratory of Integrated Service Networks Xidian University Xi’an710071 China Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada

In 2017, Zhang et al. proposed a question (not open problem) and two open problems in [IEEE TIT 63 (8): 5336–5349, 2017] about constructing bent functions by using Rothaus’ construction. In this note, we prove that the sufficient conditions of Rothaus’ construction are also necessary, which answers their question. Besides, we demonstrate that the second open problem, which considers the iterative method of constructing bent functions by using Rothaus’ construction, has only a trivial solution. It indicates that all bent functions obtained by using Rothaus’ construction iteratively can be generated from the direct sum of an initial bent function and a quadratic bent function. This directly means that Zhang et al.’s construction idea makes no contribution to the construction of bent functions. To compensate the weakness of their work, we propose an iterative construction of bent functions by using a secondary construction in [DCC 88: 2007–2035, 2020]. © 2025, CC BY-NC-ND.

关键词： Hadamard transforms

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A homogenization method for nonlinear inhomogeneous elastic materials

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Virtual Reality & Intelligent Hardware 2021年第2期3卷 156-170页

作者： Jing ZHAO Fei ZHU Liyou XU Yong TANG Sheng LI College of Information Science and Engineering Yanshan UniversityQinhuangdaoHebei 066004China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province QinhuangdaoHebei 066004China School of Electronics Engineering and Computer Science Peking UniversityBeijing 100871China Beijing Engineering Research Center for Virtual Simulation and Visualization Beijing 100871China

Background Fast simulation techniques are strongly favored in computer graphics,especially for the nonlinear inhomogeneous elastic *** homogenization theory is a perfect match to simulate inhomogeneous deformable objects with its coarse discretization,as it reveals how to extract information at a fine scale and to perform efficient computation with much less *** existing homogenization method is not applicable for ubiquitous nonlinear materials with the limited input deformation *** In this paper,we have proposed a homogenization method for the efficient simulation of nonlinear inhomogeneous elastic *** approach allows for a faithful approximation of fine,heterogeneous nonlinear materials with very coarse *** analysis provides the basis of a linear deformation space and modal derivatives extend the space to a nonlinear regime;based on this,we exploited modal derivatives as the input characteristic deformations for *** also present a simple elastic material model that is nonlinear and anisotropic to represent the homogenized *** nonlinearity of material deformations can be represented properly with this *** material properties for the coarsened model were solved via a constrained optimization that minimizes the weighted sum of the strain energy deviations for all input deformation *** arbitrary number of bases can be used as inputs for homogenization,and greater weights are placed on the more important low-frequency *** Based on the experimental results,this study illustrates that the homogenized material properties obtained from our method approximate the original nonlinear material behavior much better than the existing homogenization method with linear displacements,and saves orders of magnitude of computational *** The proposed homogenization method for nonlinear inhomogeneous elastic materials is capable of capturing the nonlinear dynamics of the

关键词： Physical-based simulation Homogenization theory Heterogeneous material Modal basis

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SFedXL: Semi-Synchronous Federated Learning With Cross-Sharpness and Layer-Freezing

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IEEE Internet of Things Journal 2025年第12期12卷 18692-18707页

作者： Zhao, Mingxiong Zhao, Shihao Feng, Chenyuan Yang, Howard H. Niyato, Dusit Quek, Tony Q. S. Yunnan University National Pilot School of Software Kunming650500 China Ministry of Education Engineering Research Center of Integration and Application of Digital Learning Technology Beijing100039 China Ministry of Education Engineering Research Center of Cyberspace Kunming650504 China Yunnan University of Finance and Economics Yunnan Key Laboratory of Service Computing Kunming650221 China EURECOM Sophia Antipolis06410 France Zhejiang University University of Illinois Urbana-Champaign Institute Zhejiang University Haining314400 China Nanyang Technological University School of Computer Science and Engineering 639798 Singapore Singapore University of Technology and Design Information Systems Technology and Design Pillar 487372 Singapore

Federated learning (FL) emerges as a potential solution for enabling multiple terminal devices to collaboratively accomplish computational tasks within an Unmanned Aerial Vehicle (UAV) swarm. However, traditional FL approaches, predicated on synchronous data aggregation, are not feasible for a UAV swarm owing to the inherently variable and dynamic nature of their communication networks compared with terrestrial systems. Furthermore, the data procured by UAVs is often highly heterogeneous, attributable to disparities in deployment environments and device attributes. Considering the distinct flight paths and unique operational conditions encountered by different UAVs, a considerable amount of data remains unlabeled. To tackle the challenges associated with asynchronous operations and the prevalence of unlabeled data, we introduce a novel framework termed Semi-synchronous FL with Cross-Sharpness and Layer-Freezing (SFedXL), tailored for a UAV swarm. In particular, we devise a cross-sharpness model training strategy aimed at optimizing the utilization of both labeled and unlabeled datasets. Additionally, we propose an innovative semi-synchronous model aggregation protocol, complemented by client-specific layer-freezing and client cluster scheduling, designed to expedite the training process. Our simulation results indicate that the proposed algorithm surpasses current FL methods in terms of object recognition accuracy and communication efficiency, albeit with a trade-off of increased local computation latency. © 2014 IEEE.

关键词： Federated learning

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FusionNet: An Effective Network Phishing Website Detection Framework Based on Multi-Modal Fusion

FusionNet: An Effective Network Phishing Website Detection F...

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IEEE International Conference on High Performance Computing and Communications (HPCC)

作者： Yu Sun Guangqi Liu Xiaohui Han Wenbo Zuo Weihua Liu Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center (National Supercomputer Center in Jinan) (Shandong Academy of Sciences) Qilu University of Technology Jinan China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China Quancheng Provincial Laboratory Jinan China

Recently, the rapid advancement of communication technology has undoubtedly improved people's lives. Unfortunately, this progress has also given rise to a significant issue: the proliferation of phishing websites. Regrettably, phishing web sites have now emerged as one of the primary threats to cybersecurity. While there have been extensive efforts to develop anti-phishing techniques, many of these approaches focus solely on a single modality of information, such as the website's URL, HTML source code, or visual features. Given the growing sophistication of phishing attacks, relying on just one modality of information is no longer sufficient to accurately identify phishing websites. To tackle this challenge, our research aims to leverage the complementarity of various modalities to enhance phishing website detection. In this paper, we introduce a multi-modal framework called FusionNet to identify phishing web pages. This framework utilizes three distinct information modalities: URLs, HTML source codes, and visual features. Specifically, our approach first designs specific representation learning architectures tailored to each modality's unique properties. Subsequently, we incorpo-rate an attention mechanism to merge these representations, thereby exploiting the synergies between the multi-modal data. The learned feature representations are more discriminative, contributing to significantly improved phishing website detection accuracy. To evaluate the performance of FusionNet, we collect a dataset comprising phishing webpages, each sample contains all three modalities-URLs, HTML source codes, and visual features. Our extensive experiments conducted on this dataset demonstrate that FusionNet outperforms state-of-the-art methods in terms of both robustness and accuracy.

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