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International Symposium on Computational Intelligence and Design, ISCID

作者： Jiaqi Liu Hongchuan Zhou Benchao Yang State Key Laboratory of Mathematical Engineering and advanced computing Information Engineering University Zhengzhou China

ISBN: (纸本)9781665438575

This paper mainly studies the change rule of center temperature of welding zone in backwelding furnace under different set temperature and transfer rate conditions, and searches for appropriate temperature and rate to obtain the optimal furnace temperature curve. Different infinite length plate models were established for the small temperature region and interval respectively, and the heat transfer of each part was considered according to Fourier heat law and Newton cooling law, and the equation about the temperature change with time was constructed based on the law of energy conservation.

关键词： Heating systems Semiconductor device modeling Temperature Cooling Furnaces Computational modeling Welding

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A Survey on Neural Machine Translation Applied to Sign Language Generation 3

A Survey on Neural Machine Translation Applied to Sign Langu...

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3rd International Conference on Applied Machine Learning, ICAML 2021

作者： Zhang, Yue Cao, Lihong State Key Laboratory of Media Convergence and Communication Communication University of China Beijing100024 China Neuroscience and Intelligent Media Institute Communication University of China Beijing100024 China State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi214125 China

ISBN: (纸本)9781665421256

Sign languages are the primary medium of communication for the deaf and hearing-impaired community, and the number of human beings with hearing impairment is increasing at a rapid rate. There is a signifîcant communication barrier between the hearing-impaired and normal-hearing communities. One solution to this issue is to offload the effort of text imderstanding for the deaf and hearing-impaired community in the form of Sign Language Generation (SLG). In this paper, first of all, we systematically review the mainstream Neural Machine Translation (NMT)based SLG approaches. Specifically, according to their model architectures, we divide them into two categories: the Recurrent Neural Networks (RNNs)-based and Transformer-based models, and discuss their advantages and limitations. Next, we introduce the existing publicly available datasets and the data pre pros ses sing methods in the field of SLG. Then, we summarize the performance evaluation methods for NMT-based SLG models. Finally, we offer two possible future research directions for better development in the field of SLG. © 2021 IEEE

关键词： Neural machine translation

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Steganalysis of adaptive JPEG steganography using 2D Gabor filters 15

Steganalysis of adaptive JPEG steganography using 2D Gabor f...

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3rd ACM Information Hiding and Multimedia Security Workshop, IH and MMSec 2015

作者： Song, Xiaofeng Liu, Fenlin Yang, Chunfang Luo, Xiangyang Zhang, Yi State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001 China Zhengzhou Information Science and Technology Institute Zhengzhou450001 China Zhengzhou Information Science and Technology Institute China State Key Laboratory of Information Assurance Beijing100072 China

ISBN: (纸本)9781450335874

Adaptive JPEG steganographic schemes are difficult to preserve the image texture features in all scales and orientations when the embedding changes are constrained to the complicated texture regions, then a steganalysis feature extraction method is proposed based on 2 dimensional (2D) Gabor filters. The 2D Gabor filters have certain optimal joint localization properties in the spatial domain and in the spatial frequency domain. They can describe the image texture features from different scales and orientations, therefore the changes of image statistical characteristics caused by steganography embedding can be captured more effectively. For the proposed feature extraction method, the decompressed JPEG image is filtered by 2D Gabor filters with different scales and orientations firstly. Then, the histogram features are extracted from all the filtered ***, the ensemble classifier is used to assemble the proposed steganalysis feature as well as the final steganalyzer. The experimental results show that the proposed steganalysis feature can achieve a competitive performance by comparing with the other steganalysis features when they are used for the detection performance of adaptive JPEG steganography such as UED, JUNIWARD and SI-UNIWARD. © 2015 ACM.

关键词： Feature extraction

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Research on Security Protocol Analysis Tool SmartVerif

Research on Security Protocol Analysis Tool SmartVerif

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2021 International Conference on Computer Technology, Information engineering and Electron Materials, CTIEEM 2021

作者： Lu, Siqi Han, Qingdi Miao, Xuyang Liu, Yubo State Key Laboratory of Mathematical Engineering and Advanced Computing Henan Zhengzhou450000 China Henan Key Laboratory of Network Cryptography Technology Henan Zhengzhou450000 China Department of Information Science and Engineering Ocean University of China Shandong Qingdao266100 China

Security protocols have been designed to protect the security of the network. However, many security protocols cannot guarantee absolute security in real applications. Therefore, security tests of the network protocol become particularly important. In this paper, firstly, we introduce SmartVerif, which is the first formal analysis tool to automatically verify the security of protocols through dynamic strategies. And then, we use SmartVerif to verify the pseudo-randomness of the encapsulated key of the Two-Pass AKE protocol, which was proposed by Liu's in ASIACRYPT in 2020. Finally, we summary our work and show some limitations of SmartVerif. At the same time, we also point out the direction for future improvement of SmartVerif. © Content from this work may be used under the terms of the Creative Commons Attribution 3.0 Licence.

关键词： Network security

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Exploration and Research of Blended Learning in the“ Principles of Computer Organization”

Exploration and Research of Blended Learning in the“ Princi...

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IEEE International Conference on Computer Science and Educational Informatization (CSEI)

作者： Yifan Hou Wei Wang Fudong Liu Zheng Shan Junchao Wang Lixin Wang State Key Laboratory of Mathematical Engineering and Advanced Computing Information Engineering University Zhengzhou China

ISBN: (数字)9781728170084

ISBN: (纸本)9781728170091

The“Principles of Computer Organization” is the core basic course for the construction of computer hardware courses. In this paper, it analyzes the characteristics of the “Principles of Computer Organization “Aiming at the challenges faced by the traditional teaching. This paper makes a beneficial exploration on the teaching reform of the Principle of Computer Composition based on the blended learning mode from the aspects of teaching content, teaching method transformation, interactive communication, evaluation and assessment, etc. This paper proposes a framework for self-learning ability training based on a blended learning model, which is applied and formed in the course of principles. Teaching practice shows that the reform of teaching mode and teaching practice not only stimulates learning interest and motivation of students, but also improves their self-learning ability and practical ability.

关键词： Education Conferences Computer science Organizations Handheld computers Voltage control

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Boosting adversarial attacks on neural networks with better optimizer

arXiv

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arXiv 2020年

作者： Yin, Heng Zhang, Hengwei Wang, Jindong Dou, Ruiyu State Key Laboratory of Mathematical Engineering and Advanced Computing Henan Zhengzhou450001 China

Convolutional neural networks have outperformed humans in image recognition tasks, but they remain vulnerable to attacks from adversarial examples. Since these data are crafted by adding imperceptible noise to normal images, their existence poses potential security threats to deep learning systems. Sophisticated adversarial examples with strong attack performance can also be used as a tool to evaluate the robustness of a model. However, the success rate of adversarial attacks can be further improved in black-box environments. Therefore, this study combines a modified Adam gradient descent algorithm with the iterative gradient-based attack method. The proposed Adam Iterative Fast Gradient Method is then used to improve the transferability of adversarial examples. Extensive experiments on ImageNet showed that the proposed method offers a higher attack success rate than existing iterative methods. By extending our method, we achieved a state-of-the-art attack success rate of 95.0% on defense models. Copyright © 2020, The Authors. All rights reserved.

关键词： Image recognition

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Research on Timestamp-based Port Hopping in Software Defined Network

Research on Timestamp-based Port Hopping in Software Defined...

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2016 3rd International Conference on engineering Technology and Application（ICETA 2016）

作者： Ziyu Zhao Wei Huang Yuanbo Guo Wei Liu State Key Laboratory of Mathematical Engineering and Advanced Computing Institute of Cryptography EngineeringInformation Engineering University

Port hopping is a typical technology in moving target defense which constantly changes communication port number to confuse potential attackers and protect target *** port hopping technology,time synchronization is the key problem to be solved since time synchronization can ensure communication port matching and avoid data loss in port hopping ***,in software defined network(SDN),since its architecture differs from traditional network,port hopping technology hasn't been fully applied in *** on timestamp synchronization,this paper creates a port hopping model in software defined network according to its centralized control,data plane and control plane separation as well as programmable *** timestampbased port hopping model,we design a three-party port synchronization mode by utilizing SDN controller and solve the problems in time synchronization such as clock drift and *** theoretical analysis and experimental results show that this proposed timestamp-based port hopping method can effectively resist Do S attack without adding load on SDN controller in software defined network.

关键词： software defined network port hopping timestamp-based synchronization handoff Clock drift DoS attack

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A Novel Timing-based Network Covert Channel Detection Method

A Novel Timing-based Network Covert Channel Detection Method

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作者： Shoupu Lu Zhifeng Chen Guangxin Fu Qingbao Li State Key laboratory of Mathematical Engineering and Advanced Computing Henan University of Economics and Law

Network stealth events are endless,and covert timing channel is one of the most difficult means to *** order to further improve the detection rate of covert timing channel,several typical network covert timing channel construction algorithms are *** the basis of the above analysis,a detection method based on IPDs multidimensional features was proposed in this *** of covert timing channels from three dimensions:shape,change rule and data statistics are ***,polarization feature,autocorrelation feature,clustering feature are proposed,and the three features are unified into a *** threshold method is used to determine whether the channel to be detected is a normal *** show that the method can detect the existing covert timing channel with less time cost and compared with the traditional detection method has a certain rate of improvement.

关键词： IPD A Novel Timing-based Network Covert Channel Detection Method

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Stealthy Malware Detection Based on Deep Neural Network

Stealthy Malware Detection Based on Deep Neural Network

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作者： Shoupu Lu Qingbao Li Xinbing Zhu State Key laboratory of Mathematical Engineering and Advanced Computing Henan University of Economics and Law

Network attacks using advanced local hiding technology have not only increased, but also become a serious threat. However, attacks using these technologies can not be detected through traffic detection, and some attacks imitate benign traffic to avoid detection. To solve these problems, a malware process detection method based on process behavior in possibly infected terminals is proposed. In this method, a deep neural network is introduced to classify malware processes. Firstly, the recurrent neural network is trained to extract the characteristics of process behavior. Secondly, training convolutional neural network is used to classify feature images generated by trained RNN features. The experiments results show that this method can effectively extract the features of malicious processes, and the AUC of ROC curve is 0.97 in the best case.

关键词： ROC image Stealthy Malware Detection Based on Deep Neural Network

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Whole-Function Vectorization Based on Simplified Openmp Directives

SSRN

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SSRN 2024年

作者： Liu, Lili Yao, Jinyang Li, Yingying Zhang, Ping Xu, Jinlong Zhao, Bo Shan, Zheng State Key Laboratory of Mathematical Engineering and Advanced Computing Henan Zhengzhou450001 China

With the continuous development of computing technology, an increasing number of vendors have integrated SIMD extension components into processors. These components can accelerate program execution efficiency and have been widely applied in various fields. Past research on SIMD components has primarily focused on loop-level and superword-level, while function-level vectorization can further exploit the parallel potential of these components, thereby enhancing application performance. Currently, OpenMP can achieve function vectorization based on directives. However, this method requires directives to be added to both the loop where the call point is located and the called functions, which is cumbersome and increases the burden on programmers. This paper proposes a directive-based function vectorization method. First, we extend the clauses in OpenMP directives concerning function vectorization data parallelism. Secondly, we implement in the compiler the functionality to automatically add corresponding directives to called functions within functions with the omp simd clone attribute and within OMP_SIMD loops. Finally, we achieve vectorization of loops containing function calls through directives. This method fully exploits the advantages of SIMD instructions, improving application performance. We selected 16 benchmarks from ISPC benchmarks and SIMD library benchmarks to evaluate our method. Experimental results show that compared to scalar, the average speedup reached 4.716x. © 2024, The Authors. All rights reserved.

关键词： Application programming interfaces (API)

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