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29th International Conference on Computational and Experimental engineering and Sciences, ICCES 2023

作者： Li, Ruixiang Feng, Xinzhu Liu, Chong Yuan, Fuxiang Ding, Shichang State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China Key Laboratory of Cyberspace Situation Awareness of Henan Province Zhengzhou China Sichuan University Chengdu China

ISBN: (纸本)9783031425141

Router-level topology, portraying the connection relationship between network devices, is important for discovering key devices in network. In actual networks, there are some anonymous routers, which do not respond traceroute due to network congestion, firewall security settings, router response rate limitations, and other factors. As these anonymous routers are difficult to eliminate, it makes the constructed router-level topology huge in size. Currently, the time cost of finding key nodes is high. Resolving anonymous nodes for reducing the topology size is necessary to improve the efficiency in finding key node. Although anonymous route resolving methods have been available, they are difficult to handle two-hop anonymous route structures in mesh topologies. To this end, based on the four structures summarized in Graph Based Induction (GBI) method, we propose a method to resolve anonymous nodes based on "watermelon patterns". Combining with Kapar, an alias IP merging method, to build router-level topologies in mesh networks. We have conducted experiments in 8 cities, such as New York, Tokyo, Seoul and so on. The experimental results show that, our method can handle the local topology containing two-hop anonymous nodes. And using our method to further reduce the size of the router-level topology built using GBI and Kapar, which is conducive to improving the efficiency of discovering key nodes in the topology. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Topology

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The exactness of the l_(1)penalty function for a class of mathematical programs with generalized complementarity constraints

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Fundamental Research 2024年第6期4卷 1459-1464页

作者： Yukuan Hu Xin Liu State Key Laboratory of Scientific and Engineering Computing Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 100049China

In a mathematical program with generalized complementarity constraints(MPGCC),complementarity relation is imposed between each pair of variable *** includes the traditional mathematical program with complementarity constraints(MPCC)as a special *** account of the disjunctive feasible region,MPCC and MPGCC are generally difficult to *** l_(1)penalty method,often adopted in computation,opens a way of circumventing the *** it remains unclear about the exactness of the l_(1)penalty function,namely,whether there exists a sufficiently large penalty parameter so that the penalty problem shares the optimal solution set with the original *** this paper,we consider a class of MPGCCs that are of multi-affine objective *** problem class finds applications in various fields,e.g.,the multi-marginal optimal transport problems in many-body quantum physics and the pricing problems in network *** first provide an instance from this class,the exactness of whose l_(1)penalty function cannot be derived by existing *** then establish the exactness results under rather mild *** results cover those existing ones for MPCC and apply to multi-block contexts.

关键词： Mathematical program with generalized complementarity constraints l_(1)penalty function Exact penalty Multi-affine objective function Error bound

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Spherical Magnetic Fe-Alginate Microgels Fabricated by Droplet-Microfluidics Combining with an External Crosslinking Approach and the Study of Their pH Dependent Fe^(3+) Release Behaviors

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Chinese Journal of Polymer Science 2025年第2期43卷 289-302页

作者： Jie Chen Run-Yu Yu ai-Qi Wang Zhe-Yu Zhang Arezoo Ardekani Yuan-Du Hu Department of Materials Science and Engineering School of Physics Science and EngineeringBeijing Jiaotong UniversityBeijing100044China Guangdong Provincial Key Laboratory of Technique and Equipment for Macromolecular Advanced Manufacturing South China University of TechnologyGuangzhou510641China State Key Laboratory of Molecular Engineering of Polymers Fudan UniversityShanghai200438China Department of Mathematics School of Mechanical EngineeringPurdue University585 Purdue MallWest LafayetteIN47907-2088USA

Due to the rapid development and potential applications of iron(Ⅲ)-alginate(Fe-Alg)microgels in biomedical as well as environmental engineering,this study explores the preparation and characterization of spherical Fe-Alg microgels using droplet microfluidics combined with an external ionic crosslinking *** study focused on the role of Fe^(3+)and examined its effects on the physical/chemical properties of microgels under different ionic conditions and reduced or oxidized *** pH-dependent release behavior of Fe^(3+)from these microgels demonstrates their potential biomedical and environmental ***,the microgels can exhibit magnetism simply by utilizing in situ oxidation,which can be further used for targeted drug delivery and magnetic separation technologies.

关键词： Fe-alginate microgels Droplet microfluidics In situ oxidation Magnetism

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Accelerating the cryo-EM structure determination in RELION on GPU cluster

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Frontiers of Computer Science 2022年第3期16卷 21-39页

作者： Xin YOU Hailong YANG Zhongzhi LUAN Depei QIAN Sino-German Joint Software Institute School of Computer Science and EngineeringBeihang UniversityBeijing 100191China State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi 214125

The cryo-electron microscopy(cryo-EM)is one of the most powerful technologies available today for structural *** RELION(Regularized Likelihood Optimization)implements a Bayesian algorithm for cryo-EM structure determination,which is one of the most widely used software in this *** researchers have devoted effort to improve the performance of RELION to satisfy the analysis for the ever-increasing volume of *** this paper,we focus on performance analysis of the most time-consuming computation steps in RELION and identify their performance bottlenecks for specific *** propose several performance optimization strategies to improve the overall performance of RELION,including optimization of expectation step,parallelization of maximization step,accelerating the computation of symmetries,and memory affinity *** experiment results show that our proposed optimizations achieve significant speedups of RELION across representative *** addition,we perform roofline model analysis to understand the effectiveness of our optimizations.

关键词： cryo-EM structure determination performance optimization GPU acceleration RELION

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Packet Modification and Utilization Technology of SOHO Router 2

Packet Modification and Utilization Technology of SOHO Route...

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2nd International Conference on advanced Manufacturing Technology and Manufacturing Systems, ICAMTMS 2023

作者： Gai, Xianzhe Cai, Ruijie Jia, Fan Chen, Hongwei Yang, Pengfei Liu, Shengli State Key Laboratory of Mathematical Engineering and Advanced Computing 62 Science Ave. Zhengzhou450001 China

ISBN: (纸本)9781510667327

As a gateway to handle all intranet terminal traffic, SOHO router plays an important role in the network. In this paper, we introduced the security threats faced by SOHO routers, and on this basis, we propose a packet modification method of " Discard-Resend". The method does not affect the normal operation of the router, nor does it affect the normal communication between the two sides. We have done experiments on this packet modification method in several scenarios from the view of network security personnel and network attackers, and achieved the desired results. The packet modification method of " Discard-Resend" is a basic work in the security research of SOHO router, and it is of great significance. © 2023 SPIE.

关键词： Network security

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A Review of Few-Shot Network Traffic Classification Based on Deep Learning

A Review of Few-Shot Network Traffic Classification Based on...

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2023 International Conference on Mechatronics and Intelligent Control, ICMIC 2023

作者： Yang, Kai Wang, Ruo Nan Meng, Qi Meng, Long Qi, Zan Li, Xue Fei, Jin Long State Key Laboratory of Mathematical Engineering And Advanced Computing PLA Strategic Support Force Information Engineering University Zhengzhou China

ISBN: (纸本)9781510668393

At present, deep learning has achieved excellent performance in the field of network traffic classification. However, deep learning relies on massive data-driven classification models. When the data set is small, it is usually hindered. In order to solve this problem, few-shot network traffic classification technology based on deep learning has been gradually studied. In this paper, we conducted a comprehensive survey to fully understand the few-shot traffic classification techniques. We first define the few-shot traffic classification problem. Based on how to solve the contradiction between the few-shot data set and the large number of parameters to be trained in the model, we classify the current few-shot traffic classification method based on deep learning from two perspectives: (1) Data augmentation method, which uses the method of expanding the data set to enhance the supervision experience. In this paper, the methods based on data enhancement are divided into two categories based on GAN and feature transformation.(2) Model-based methods. Model-based methods are divided into three categories: transfer learning, metric learning and meta-learning. And discuss the advantages and disadvantages of each classification method. Finally, the results are summarized and the future development direction of few-shot network traffic classification technology based on deep learning is prospected. © 2023 SPIE.

关键词： Deep learning

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The convergence properties of infeasible inexact proximal alternating linearized minimization

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Science China mathematics 2023年第10期66卷 2385-2410页

作者： Yukuan Hu Xin Liu State Key Laboratory of Scientific and Engineering Computing Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China School of Mathematical Sciences University of Chinese Academy of SciencesBeijing 100049China

The proximal alternating linearized minimization(PALM)method suits well for solving blockstructured optimization problems,which are ubiquitous in real *** the cases where subproblems do not have closed-form solutions,e.g.,due to complex constraints,infeasible subsolvers are indispensable,giving rise to an infeasible inexact PALM(PALM-I).Numerous efforts have been devoted to analyzing the feasible PALM,while little attention has been paid to the *** usage of the PALM-I thus lacks a theoretical *** essential difficulty of analysis consists in the objective value nonmonotonicity induced by the *** study in the present work the convergence properties of the *** particular,we construct a surrogate sequence to surmount the nonmonotonicity issue and devise an implementable inexact *** upon these,we manage to establish the stationarity of any accumulation point,and moreover,show the iterate convergence and the asymptotic convergence rates under the assumption of the Lojasiewicz *** prominent advantages of the PALM-I on CPU time are illustrated via numerical experiments on problems arising from quantum physics and 3-dimensional anisotropic frictional contact.

关键词： proximal alternating linearized minimization infeasibility nonmonotonicity surrogate sequence inexact criterion iterate convergence asymptotic convergence rate

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Adversarial Example Attacks Against Intelligent Malware Detection: A Survey 4

Adversarial Example Attacks Against Intelligent Malware Dete...

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4th International Conference on Applied Machine Learning, ICAML 2022

作者： Qi, Xuyan Tang, Yonghe Wang, Huanwei Liu, Tieming Jing, Jing State Key Laboratory of Mathematic Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781665462655

With the advancement of information technology and the increasing prevalence of the internet, the number of malware has experienced an exponential, and the security threat to users' property and privacy is becoming more serious. With the great success of artificial intelligence especially deep learning technology in fields such as computer vision and speech processing, deep learning are gradually introduced into the field of malware detection, to process large amounts of malware more efficiently. However, in recent years, researchers have discovered that the deep learning model itself also has security risks. While malware detection based on deep learning brings convenience and technical progress, it also introduces some new threats, such as adversarial examples. This paper investigates adversarial example attacks against deep learning-based malware detectors. First, We reviewed research on malware detection techniques. Then we analyze the works related to adversarial example attacks against intelligent malware detectors. Finally, we discuss the challenges and prospects in future research. © 2022 IEEE.

关键词： Malware

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A review of auxiliary hardware architectures supporting dynamic taint analysis

A review of auxiliary hardware architectures supporting dyna...

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2022 International Conference on Cloud computing, Internet of Things, and Computer Applications, CICA 2022

作者： Yang, Anfeng Guang, Yan Zhao, Yuntian State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781510656673

Dynamic taint analysis is a widely used information flow analysis method. The software structure supporting dynamic taint analysis needs running program to monitor the spread of taint, which will bring a large running time overhead. The architecture based on hardware implementation can shorten the running time overhead of taint analysis through hardware modification, which has great research significance. Firstly, we introduced the research background and significance of hardware. Then, we describe the problems of providing support structure for dynamic taint analysis based on software and how to solve or alleviate these problems in hardware architecture on the basis of the introduction of the specific classification and structure of hardware architecture. Finally, on the basis of comparing the characteristics of hardware structure from different dimensions, the future research direction of hardware structure is prospected. © 2022 SPIE.

关键词： Memory architecture

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A Malware Classification Method based on Attentive Bidirectional Model 7

A Malware Classification Method based on Attentive Bidirecti...

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7th International Conference on Intelligent computing and Signal Processing, ICSP 2022

作者： Gui, Hairen Liu, Fudong Zhang, Chunyan Tang, Ke State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781665478571

Deep learning techniques have achieved significant improvements in malware analysis application, such as malware detection, malware classification and vulnerability mining. Convolutional neural network (CNN) is applied to extract local features of samples, while recurrent neural network (RNN) mainly extracts global features from sequence context. However, the pooling layer in CNN is a nonlinear dimensionality reduction operation, which can cause a loss of correlation feature. The raw RNN or LSTM model cannot perform parallel computing when calculating the feature vectors, limiting the effect of model application. Hence, we propose a novel malware classification model named BGSA (Bidirectional GRU with Self- Attention), which applies bi-direction gated recurrent unit (BiGRU) and self-attention mechanism. To demonstrate that the model can improve the feature extraction capability, a series of comparison experiments have been conducted on the VxHeavon dataset. The results show that the classification of BGSA reaches 92.54% in term of precision, which surpass the performance of method based on LSTM+CNN and BiGRU. © 2022 IEEE.

关键词： Long short-term memory

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