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2nd International Conference on Computer Science and Educational Informatization, CSEI 2020

作者： Liu, Fudong Zhang, Ping Hou, Yifan Wang, Lixin Shan, Zheng Wang, Junchao State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (数字)9781728170084

ISBN: (纸本)9781728170077

In recent years, a large number of malware has spread indiscriminately, which causes various significant cyberspace security incidents all over the world. Therefore, malware detection has become one of the important research topics in cyberspace security. At present, however, the practical teaching for malware detection mainly focuses on delivering the theory and skills, and actual combat training is relatively weak. As a novel method for malware recognition and analysis, software gene technology can quickly explore potential functional and behavioral information of malware, and detect unknown malware. Hence, building an experimental platform for malware gene analysis can effectively reduce the time required for students to quickly carry out the actual analysis process, support student needs for comprehensive data analysis, and provide a unified public service infrastructure for classroom teaching, practical training and scientific research. © 2020 IEEE.

关键词： Genes

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Stability Analysis of a Rumor Propagation Model in Complex Networks with Holling II Type Functional Response 6

Stability Analysis of a Rumor Propagation Model in Complex N...

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6th International Conference on Big Data and Information Analytics, BigDIA 2020

作者： Yu, Ze Zhou, Gang Luo, Junyong Zhang, Mengli Huang, Ningbo State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

In this paper, we propose a SH2I2 rumor propagation model considering self-learning mechanism and echo chamber situation with Holling type II functional response in homogeneous and heterogeneous networks. Firstly, we obtain the basic reproduction number through Jacobian Matrix method and calculate the equilibrium points. Secondly, we prove the existence of rumor-prevailing equilibrium point as well as the local and globally stabilities by Routh-Huiwitz judgment and Lyapunov function. Finally, we use theoretical analysis and numerical simulations to investigate the effect of parameters for suppressing the prevalence of rumors. © 2020 IEEE.

关键词： Heterogeneous networks

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Memory Error Detection Based on Dynamic Binary Translation 20

Memory Error Detection Based on Dynamic Binary Translation

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20th IEEE International Conference on Communication Technology, ICCT 2020

作者： Xu, Hang Ren, Wei Liu, Zimian Chen, Jiajun Zhu, Junhu State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781728181417

Dynamic memory error detection technology is widely utilized in locating and mitigating memory-corruption vulnerabilities. High false negative in existing technologies impairs the effectiveness of detection, especially when the detector has no source code. We proposed a dynamic memory error detection method based on dynamic binary translation. It realized the detection by combining a call stack tracing method and an IR language level memory error detection method. Experiments show that the detection success rate of this method in the heap and stack memory destruction is more than 80%. © 2020 IEEE.

关键词： Error detection

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Moving Target Defense Decision-Making Method: A Dynamic Markov Differential Game Model 7

Moving Target Defense Decision-Making Method: A Dynamic Mark...

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7th ACM Workshop on Moving Target Defense, MTD 2020

作者： Zhang, Hengwei Tan, Jinglei Liu, Xiaohu Wang, Jindong State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781450380850

Today most of the moving target defense decision-making methods are based on models of a discrete dynamic game. To more accurately study network attack-defense strategies against continuous confrontations, we analyze offensive and defensive behavior from a dynamic perspective. We propose a moving target defense decision-making method based on a model of a dynamic Markov differential game. We implement dynamic analysis and deduction of multi-stage continuous attack and defense confrontations for scenarios of continuous real-Time network attack-defense. We take into account the influence of random factors and changes of the network system in the gaming process, combine differential gaming with the Markov decision-making method, and construct models of attack-defense games. We propose a solution for game equilibrium based on an objective function designed according to the total discounted payoff of the offensive and defensive game and the analysis of the characteristics of multi-staged game equilibrium. On this basis an optimal strategy selection method is designed. We apply and verify the game model and the defense strategy selection algorithm by using the moving target defense technique. We conduct simulations to verify the effectiveness and feasibility of the model and algorithm. © 2020 ACM.

关键词： Decision making

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Software supply chain analysis based on function similarity 4

Software supply chain analysis based on function similarity

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2020 4th International Conference on Electrical, Mechanical and Computer engineering, ICEMCE 2020

作者： Sun, Wenjie Shan, Zheng Liu, Fudong Li, Xingwei Qiao, Meng Zhang, Chunyan State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

The supply of open source and open source components is growing at an alarming rate, while vulnerabilities in open source components are everywhere. Software supply chain analysis aims to discover third-party components and open source code used in a software, and analyze the software's dependence on components. In this paper, we propose a software component analysis method and a known vulnerabilities detecting method. By scanning the open source components of the binary file and conducting vulnerability analysis, the known vulnerabilities are detected. This paper mainly solves the problem of detecting known vulnerabilities in the supply chain of binary files. We conducted a case analysis and achieved good results. © 2020 Institute of Physics Publishing. All rights reserved.

关键词： Supply chains

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Thinking and practice of online teaching under COVID-19 Epidemic 2

Thinking and practice of online teaching under COVID-19 Epid...

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2nd International Conference on Computer Science and Educational Informatization, CSEI 2020

作者： Ping, Zhang Fudong, Liu Zheng, Shan State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781728170077

Response to the outbreak of COVID-19, classes in this semester are mainly replaced by online teaching to ensure continual learning. Teachers are actively exploring effective online teaching methods to provide a good learning experience for students at home. This paper presents an online teaching model based on the idea of Problem-Based Learning (PBL) and take 'Data Structure' as an example to discuss the design of teaching process and problems. © 2020 IEEE.

关键词： COVID-19

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Security-as-a-Service with Cyberspace Mimic Defense Technologies in Cloud 7th

Security-as-a-Service with Cyberspace Mimic Defense Technolo...

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7th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2021

作者： Wang, Junchao Pang, Jianmin Wei, Jin State Key Laboratory of Mathematical Engineering and Advanced Computing ZhengZhou China School of Computer Science Fudan University Shanghai China Shanghai Key Laboratory of Data Science Fudan University Shanghai China

ISBN: (纸本)9789811659423

Users usually focus on the application-level requirements which are quite friendly and direct to them. However, there are no existing tools automating the application-level requirements to infrastructure provisioning and application deployment. Although some security issues have been solved during the development phase, the undiscovered vulnerabilities remain hidden threats to the application’s security. Cyberspace mimic defense (CMD) technologies can help to enhance the application’s security despite the existence of the vulnerability. In this paper, the concept of SECurity-as-a-Service (SECaaS) is proposed with CMD technologies in cloud environments. The experiment on it was implemented. It is found that the application’s security is greatly improved to meet the user’s security and performance requirements within budgets through SECaaS. The experimental results show that SECaaS can help the users to focus on application-level requirements (monetary costs, required security level, etc.) and automate the process of application orchestration. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Budget control

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Attention-aligned mean-teacher learning for unsupervised domain adaptive person re-ID

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Science China Technological Sciences 2025年

作者： You LYU Zhen ZHANG Guoliang KANG Wei WEI Institute of Artificial Intelligence Beihang University Key Laboratory of Mathematics Informatics Behavioral Semantics Ministry of Education Beihang University State Key Laboratory of Software Development Environment and Advanced Innovation Center for Future Blockchain and Privacy Computing Beihang University School of Automation Science and Electrical Engineering Beihang University AVICAS Generic Technology Co. Ltd Zhongguancun Laboratory School of Mathematics Sciences Beihang University

In recent years, artificial intelligence has fueled the development of numerous applications [1, 2]. Person re-identification (re-ID) is a typical artificial intelligence system designed to automatically retrieve imag...

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An Extraction Method of Network Security Situation Elements Based on Gradient Lifting Decision Tree

An Extraction Method of Network Security Situation Elements ...

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advanced computing and Endogenous Security, International Conference on

作者： Zhaorui Ma Shicheng Zhang Yiheng Chang Qinglei Zhou Xinhao Hu Xia Li State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China Zhengzhou University of Light Industry Zhengzhou China

ISBN: (纸本)9781665424509

The primary purpose of acquiring network security situation elements is to detect and discover potential security threats from discrete and isolated data. In the complex network environment, the existing network security situation element acquisition technology has the problems of low extraction accuracy and low extraction efficiency. To solve these problems, a method for extracting network security situation elements based on Gradient Boosting Decision Tree (GBDT) is proposed. This method uses the attribute reduction function of rough set to preprocess the original data, which can effectively reduce redundancy. Furthermore, the initial parameters of GBDT are optimized by quantum particle swarm optimization (QPSO) algorithm to improve stability. Finally, the optimized GBDT classifier is used to classify and train with the reduced data set, and the accuracy of the final classifier is continuously improved by reducing the deviation via iterative optimization. Experiments demonstrate that the proposed algorithm achieves significant results and outperforms several state-of-the-art algorithms to the extraction of network security situation elements on the UNSW-NB15 dataset.

关键词： Termination of employment Rough sets Complex networks Network security Stability analysis Classification algorithms Decision trees

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RaCMC: Residual-Aware Compensation Network with Multi-Granularity Constraints for Fake News Detection 39

RaCMC: Residual-Aware Compensation Network with Multi-Granul...

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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

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 Guangzhou 510006 China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou 450002 China State Key Laboratory of Internet of Things for Smart City Department of Computer and Information Science Faculty of Science and Technology University of Macau 999078 Macao

ISBN: (纸本)157735897X

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. © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Modal analysis

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