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16th IEEE International Wireless Communications and Mobile computing Conference, IWCMC 2020

作者： Chen, Ling Liu, Wenwen Gong, Daofu Chen, Yan State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450002 China

ISBN: (纸本)9781728131290

The Cluster-based Routing Algorithm for Wireless Sensor Network based on Subtractive Clustering (SCC algorithm) generates nodes of cluster head in dense area of the node by relying on subtractive clustering. The application of this algorithm effectively solves the attribution problem of non-cluster head node in conventional algorithms, and consumption is evenly distributed throughout the network. Through simulation experiments, it can be found that the application of the SCC algorithm can map the distribution of nodes of cluster head reasonably and delay the death time of the first node to prolong the lifetime of network and balance the energy consumption of nodes. © 2020 IEEE.

关键词： Routing algorithms

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Research on the Protection Mechanism of Cisco IOS Exploit 4

Research on the Protection Mechanism of Cisco IOS Exploit

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4th International Conference on Data Mining, Communications and Information Technology, DMCIT 2020

作者： Wang, Jinzhu Cai, Ruijie Liu, Shengli State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001 China

Cisco IOS is an operating system that runs on Cisco routing and switching equipment. Its security is important to the entire network. Since vulnerability attacks have become one of the main sources of threat to Cisco IOS security, it is necessary to analyze the defense mechanism of IOS against vulnerability attacks. The purpose of this paper is to find out the deficiencies of IOS vulnerability defense mechanism in time and put forward improvement methods and preventive measures. Firstly, this paper introduces the protection mechanism of Cisco IOS vulnerability, including CheckHeaps, DEP, ASLR. The principle of these mechanisms and the idea of vulnerability protection are analyzed. And then, after analyzing the shortcomings of these protection mechanisms, the basic idea of bypassing these protection mechanisms is proposed. Finally, in view of the shortcomings of Cisco IOS vulnerability defense mechanism and the proposed bypass methods, some advices about how to better protect Cisco IOS from vulnerability exploitation are given. © Published under licence by IOP Publishing Ltd.

关键词： Network security

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An evaluation algorithm of the importance of network node based on community influence 1

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5th International Conference on Data Mining and Big Data, DMBD 2020

作者： He, Gongzhen Luo, Junyong Yin, Meijuan State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001 China

ISBN: (数字)9789811572050

ISBN: (纸本)9789811572043

Identifying nodes in social networks that have great influence on information dissemination is of great significance for monitoring and guiding information dissemination. There are few methods to study the influence of communities on social networks among the existing node importance evaluation algorithms, and it is difficult to find nodes that promote information dissemination among communities. In view of this reason, this paper proposes a node importance evaluation algorithm based on community influence (abbreviated as IEBoCI algorithm), which evaluates the importance of the nodes based on the influence degree of the nodes on the communities and the ability to disseminate information the communities to which the nodes are connected. This algorithm firstly calculates the activation probability of nodes to other nodes, which is used to divide communities and evaluate influence. Secondly, the network is divided into communities based on LPA algorithm. Finally, the importance of the node is calculated by combining the influence of the community itself and the influence of the node on the community. Experiments are carried out on real social network data and compared with other community-based methods to verify the effectiveness of the algorithm. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Complex networks

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Defense method of ruby code injection attack based on instruction set randomization 20

Defense method of ruby code injection attack based on instru...

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8th International Conference on Computer and Communications Management, ICCCM 2020

作者： Wang, Jiang Yao, Yuan Zhang, Gaofei Li, Fangyun State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001 China

ISBN: (纸本)9781450387668

Code injection attack is a major security threat to applications, especially web applications. This type of attack stems from the attacker's ability to use the vulnerability/backdoor of the application to inject a malicious program into the server and execute it, or the application's lack of verification and filtering of user input parameters, resulting in the input being executed as a malicious program to achieve the attack aims. The existing defense methods, such as source program analysis and input rule matching, have inherent defects in the face of code injection attacks. In order to improve the defense effect of web applications against code injection attacks, a method against code injection based on instruction set randomization was proposed. The defense method does not depend on the attack method adopted by the attacker, and can resist unknown code injection attacks. Based on this technology, the concept of dynamic transformation is introduced to improve the defense ability. Even if the attacker obtains the randomization method, it is difficult to break through the system. Although this method requires randomized transformation of the application source code, the processing process is completely automated. Experiments show that this method can effectively resist code injection attacks and achieve active defense against attacks. © 2020 ACM.

关键词： Network security

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Network representation learning based extended matrix factorization for recommendation 6th

Network representation learning based extended matrix factor...

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6th International Conference on Artificial Intelligence and Security,ICAIS 2020

作者： Xu, Jinmao Gong, Daofu Liu, Fenlin Tan, Lei State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001 China

ISBN: (纸本)9789811581007

The growing heterogeneous data in the Internet effectively improves the performance of recommender systems (RS). The main problem faced by the traditional matrix factorization (MF) is how to fuse more heterogeneous information data in MF to improve the performance of RS. In view of this, this paper proposes an Extended Matrix Factorization (EMF) based on network representation learning. EMF integrates multiple types of data in Heterogeneous Information Network (HIN) to improve the accuracy of prediction rating. The nodes in HIN are first mapped to a low-dimensional representation vector by network representation learning (NRL). Then the representation vector is used as the input of the EMF, the parameters are optimized by the gradient descent, and finally the prediction model is obtained. The experiments on two real data sets show the effectiveness of the EMF. Compared with the baseline algorithms, the EMF model can obtain more accurate prediction rating. © Springer Nature Singapore Pte Ltd 2020.

关键词： Recommender systems

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Network security assessment based on full host-based attack graph

Network security assessment based on full host-based attack ...

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2020 International Conference on Cyberspace Innovation of advanced Technologies, CIAT 2020

作者： Wang, Xiao-Fan Zhou, Tian-Yang Zhu, Jun-Hu State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou Henan China

ISBN: (纸本)9781450387828

Network security assessment is an important method of evaluating network security. The existing researches of network security assessment have the problem that the method is not comprehensive and accurate. In order to solve this problem, we proposed a method of network security assessment based on a full host-based attack graph from the "point"and "plane"perspective. This method constructed a full host-based attack graph model, and proposed a splitting algorithm for weakly connected components of the full host-based attack graph. The algorithm is used to evaluate the network security from the "plane"perspective. Meanwhile, based on the full host-based attack graph and the theory of degree centrality and betweenness centrality, the key nodes in the network are evaluated. Therefore, this method accomplished the comprehensive and accurate security measurement of the network. The experimental results showed the effectiveness of the method. © 2020 ACM.

关键词： Network security

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Dynamic Network Change Detection via Dynamic Network Representation Learning 14th

Dynamic Network Change Detection via Dynamic Network Represe...

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14th EAI International Conference on Communications and Networking in China, ChinaCom 2019

作者： Feng, Hao Liu, Yan Zhou, Ziqiao Chen, Jing China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9783030411138

The structure of the network in the real world is very complex, as the dynamic network structure evolves in time dimension, how to detect network changes accurately and further locate abnormal nodes is a research hotspot. Most current feature learning methods are difficult to capture a variety of network connectivity patterns, and have a high time complexity. In order to overcome this limitation, we introduce the network embedding method into the field of network change detection, we find that node-based egonet can better reflect the connectivity patterns of the node, so a dynamic network embedding model Egonet2Vec is proposed, which is based on extracting the connectivity patterns of the node-based egonets. After the dynamic network representation learning, we use a dynamic network change detection strategy to detect network change time points and locate abnormal nodes. We apply our method to real dynamic network datasets to demonstrate the validity of this method. © 2020, ICST Institute for Computer Sciences, Social Informatics and Telecommunications engineering.

关键词： Change detection

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Clustering and Routing Optimization Algorithm for Heterogeneous Wireless Sensor Networks 16

Clustering and Routing Optimization Algorithm for Heterogene...

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16th IEEE International Wireless Communications and Mobile computing Conference, IWCMC 2020

作者： Chen, Ling Liu, Wenwen Gong, Daofu Chen, Yan State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450002 China

ISBN: (纸本)9781728131290

Wireless sensor network (WSN) is the cutting-edge technology of modern monitoring technology. There is a direct relationship between the length of its lifetime and its performance. Efficient and reasonable clustering and routing algorithm can reduce the energy loss in the network, which is of great significance for prolonging the network lifetime. The traditional WSN protocol has been difficult to meet the needs of the contemporary society. This paper focuses on the advantages and disadvantages of the traditional WSN protocol, and puts forward relevant improvement measures to optimize the traditional WSN protocol and extend the network life time. © 2020 IEEE.

关键词： Wireless sensor networks

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Research on 3D Human Body Reconstruction Algorithm of Monocular Image 5

Research on 3D Human Body Reconstruction Algorithm of Monocu...

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5th Asian Conference on Artificial Intelligence Technology, ACAIT 2021

作者： Liang, Zijian Liang, Huan Fu, Wenlong Neuroscience and Intelligent Media Institute Communication University of China Beijing China State Key Laboratory of Media Convergence and Communication Communication University of China Beijing China State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi China

ISBN: (纸本)9781665426305

The three-dimensional human body feature parameters extracted by the neural network method are coupled in the high-dimensional feature space. The fully connected network processes the three-dimensional human pose and shape feature information synchronously, which cannot handle multifactor features well, which makes the model perform poorly. To solve this problem, on the basis of the benchmark network, a decoupling model is added, which processes the three-dimensional human pose and shape information separately, and finally integrates the features through the bi-linear transformation method. Through experimental verification, the algorithm effectively reduces the reconstruction error, and the improved algorithm performs better. © 2021 IEEE.

关键词： Three dimensional computer graphics

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RaCMC: Residual-Aware Compensation Network with Multi-Granularity Constraints for Fake News Detection

arXiv

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arXiv 2024年

作者： Yu, Xinquan Sheng, Ziqi Lu, Wei Luo, Xiangyang Zhou, Jiantao School of Computer Science and Engineering Ministry of Education Key Laboratory of Information Technology Guangdong Province Key Laboratory of Information Security Technology Sun Yat-sen University Guangzhou510006 China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450002 China State Key Laboratory of Internet of Things for Smart City The Department of Computer and Information Science Faculty of Science and Technology University of Macau 999078 China

Multimodal fake news detection aims to automatically identify real or fake news, thereby mitigating the adverse effects caused by such misinformation. Although prevailing approaches have demonstrated their effectiveness, challenges persist in cross-modal feature fusion and refinement for classification. To address this, we present a residual-aware compensation network with multi-granularity constraints (RaCMC) for fake news detection, that aims to sufficiently interact and fuse cross-modal features while amplifying the differences between real and fake news. First, a multiscale residual-aware compensation module is designed to interact and fuse features at different scales, and ensure both the consistency and exclusivity of feature interaction, thus acquiring high-quality features. Second, a multi-granularity constraints module is implemented to limit the distribution of both the news overall and the image-text pairs within the news, thus amplifying the differences between real and fake news at the news and feature levels. Finally, a dominant feature fusion reasoning module is developed to comprehensively evaluate news authenticity from the perspectives of both consistency and inconsistency. Experiments on three public datasets, including Weibo17, Politifact and GossipCop, reveal the superiority of the proposed method. Copyright © 2024, The Authors. All rights reserved.

关键词： Fake detection

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