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Model for Software Behaviour Detection Based on Process Algebra and system Call

China Communications 2013年第11期10卷 24-36页

作者：申利民王涛马川 College of Information Science and Engineering Yanshan University The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Hebei Normal University of Science and Technology

Behaviour detection models based on automata have been studied widely. By add- ing edge ε, the local automata are combined into global automata to describe and detect soft- ware behaviour. However, these methods in- troduce nondeterminacy, leading to models that are imprecise or inefficient. We present a model of software Behaviour Detection based on Process Algebra and system call （BDPA）. In this model, a system call is mapped into an action, and a function is mapped into a process We construct a process expression for each function to describe its behaviour. Without con- strutting automata or introducing nondeter- minacy, we use algebraic properties and algo- rithms to obtain a global process expression by combining the process expressions derived from each function. Behaviour detection rules and methods based on BDPA are determined by equivalence theory. Experiments demon- strate that the BDPA model has better preci- sion and efficiency than traditional methods.

关键词： intrusion detection software be-haviour model static analysis process algebra system call

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A sketch recognition method based on bi-modal model using cooperative learning paradigm

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Neural Computing and Applications 2024年第23期36卷 14275-14290页

作者： Zhang, Shihui Wang, Lei Cui, Zhiguo Wang, Shi School of Information Science and Engineering Yanshan University Hebei Street West Section Hebei Province Qinhuangdao066000 China Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Yanshan University Hebei Street West Section Hebei Province Qinhuangdao066000 China School of Information Technology Hebei University of Business and Economics Xuefu Road Hebei Province Shijiazhuang050061 China School of Mathematics and Information Science and Technology Hebei Normal University of Science and Technology Hebei Street West Section Hebei Province Qinhuangdao066000 China

Static image is an important form of displaying a sketch, representing the appearance information of the sketch. And a stroke sequence composed of several points can also express the shape and contour information of the sketch. Therefore, it is very reasonable to treat a sketch as point-modal data and image-modal data simultaneously. In this paper, a method based on bi-modal model using cooperative learning paradigm is proposed for the sketch recognition task. Specifically, in the point-modal branch, a structural point convolution block is developed by properly dividing local regions to preserve the structural information. In the image-modal branch, the hierarchical residual structure is used to fully extract image-modal features. To reduce the negative impact of noisy samples on the recognition performance, a cooperative learning paradigm is designed based on different perceptual abilities of two modal branches on noisy samples, that is, when training the two branches, the noisy samples can be filtered out through information exchanges and mutual learning. Extensive experiments on the sketch datasets TU-Berlin and QuickDraw show that the proposed method outperforms most baseline methods and has many advantages such as no dependence on additional data and stroke information. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Convolution

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Edge collapse mesh simplification algorithm based on detail features preserving

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Journal of Computational Information systems 2014年第7期10卷 2883-2890页

作者： Jia, Qi Liu, Yongshan Gu, Xiaoying College of Information Science and Engineering Yanshan University Qinhuangdao 066004 China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Yanshan University Qinhuangdao 066004 China Data Industry Research Lab. Qinhuangdao 066004 China

The existing model simplification algorithm in simplified speed and quality can't reach a better compromise, so we present an improved quadric error metrics edge collapse mesh simplification algorithm. This algorithm makes the local region unevenness of vertex, the local region average area of vertex and edge length as constraint factors add to the edge collapse cost, by changing the order of the edge collapse to retain the important detail features of the original model. New vertex position is calculated on the different types of edge, keeping the boundary characteristics of the mesh model. Experimental results show that the improved algorithm not only runs faster, but also maintains a higher degree on the model feature region. © 2014 Binary Information Press.

关键词： Mesh generation

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Research on Software Community Division Method Based on Inter-node Dependency 16th

Research on Software Community Division Method Based on Inte...

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16th International Conference on Intelligent Computing, ICIC 2020

作者： Dong, Jun Hao, Chengqian Ren, Jiadong Lu, Haitao College of Information Science and Engineering Yanshan University Qinhuangdao066000 China The Key Computer Virtual Technology and System Integration Laboratory of Hebei Province Qinhuangdao066000 China

ISBN: (纸本)9783030607982

The mining of software community structure is of great significance in identifying software design pattern, software maintenance, software security and optimizing software structure. To improve the accuracy of description of software execution status model, A new method to construct merge software execute graph is proposed that based on the software execution network model. And then to get the software execution path through the software execution sequence analysis, The ND (Node Dependence) was proposed to measure the tightness of inter-node dependencies based on the design principle of "high cohesion, low coupling" of software. At last, depends on the software execution path, the SLCA (Software Label Communities Algorithm) community division algorithm is proposed to improve stability of community partition algorithm and validity of software module partition. © 2020, Springer Nature Switzerland AG.

关键词： Complex networks

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The study of a hierarchical hadoop architecture in multiple data centers environment

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Open Cybernetics and systemics Journal 2015年第1期9卷 131-137页

作者： Shengtao, Sun Aizhi, Wu Xiaoyang, Liu School of Information Science and Engineering Yanshan University QinhuangdaoHebei066004 China College of Vehicles and Energy Yanshan University QinhuangdaoHebei066004 China Data Industry Research Institute Limited Company QinhuangdaoHebei066004 China Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province QinhuangdaoHebei066004 China

Hadoop is a reasonable tool for cloud computing in big data era and MapReduce paradigm may be a highly successful programming model for large-scale data-intensive computing application, but the conventional MapReduce model and Hadoop framework limit themselves to implement jobs within single cluster. Traditional single-cluster Hadoop may not suitable for situations when data and compute resources are widely distributed this paper focuses on the application of Hadoop across multiple data centers and clusters. A hierarchical distributed computing architecture of Hadoop is designed and the virtual Hadoop file system is proposed to provide global data view across multiple data centers. The job submitted by user can be decomposed automatically into several sub-jobs which are then allocated and executed on corresponding clusters by location-aware manner. The prototype based on this architecture shows encouraging results. © Shengtao et al.

关键词： MapReduce

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Research on the Influence of Improved K-shell Algorithm on Commodity Profit 2

Research on the Influence of Improved K-shell Algorithm on C...

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2nd International Conference on Artificial Intelligence and computer Science, AICS 2020

作者： Chen, Jing Huang, Jincheng College of Information Science and Engineering Yanshan University Qinhuangdao066004 China Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao066004 China Software Engineering Laboratory in Hebei Province Qinhuangdao066004 China

In order to maximize the influence of commodity profits in e-commerce platforms, designing and improving the K-shell algorithm to select the more influential seed node sets in this paper. The new algorithm improves the number of active nodes by setting node threshold and edge weight attributes. To obtain more commodity profits, a strategy IRDSN (Strategy for Improving Repeat Degree of Seed Nodes) is proposed to select initial seed nodes and improve the repeat degree of seed nodes. The profit maximization based on linear threshold model is realized by setting different propagation modes. The improved algorithm and strategy IRDSN are analysed and verified in real data set and e-commerce platform. The results show that the algorithm effectively improves the profit of commodities. © Published under licence by IOP Publishing Ltd.

关键词： Profitability

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Research on a Novel Influence Maximization Algorithm Based on Community Structure 2

Research on a Novel Influence Maximization Algorithm Based o...

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2nd International Conference on Artificial Intelligence and computer Science, AICS 2020

作者： Chen, Jing Liu, Jiangchuan College of Information Science and Engineering Yanshan University Qinhuangdao066004 China Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao066004 China Software Engineering Laboratory in Hebei Province Qinhuangdao066004 China

With the research of influence maximization algorithm, many researchers have found that the existing algorithm has the problem of overlapping influence of seed nodes. In order to solve the problem of overlapping influence of seed nodes, this paper proposes an IMCS algorithm based on community structure. Firstly, we divide the community through the central node, and the quality of community division is ensured by defining community fitness and node contribution. Then through the analysis of the community division results, the seed node selects the one with the largest degree. Since most of the nodes activated by seed nodes of different communities also belong to different communities, this method solves the problem of overlapping influence to a certain extent. The experimental results show that the effectiveness of the IMCS algorithm is verified under the real network, cooperative network and artificial network, and the IMCS algorithm has a better effect than IEIR and Degree algorithms in most networks under the IC model. © Published under licence by IOP Publishing Ltd.

关键词： community division community structure independent cascade model influence maximization overlapping influence Seed node

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Learning to Cluster Person in the Video via Graph Convolution Network 13

Learning to Cluster Person in the Video via Graph Convolutio...

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13th International Conference on Information technology in Medicine and Education, ITME 2023

作者： Li, Wei Liang, Sixin Bian, Ang Du, Guodong College of Computer Science Sichuan University Chengdu China School of Information Science and Engineering Yanshan University The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao China

ISBN: (纸本)9798350319156

Video person re-identification is receiving academic interest. However, the practical application of the algorithm is hardly supported because of prohibitive annotated data. Hence, the study for unlabeled data will lead to an attractive alternative. This work explores an innovative strategy, namely, learning to cluster unlabeled person in the video through graph convolutional networks. In this paper, we find that the possibility of inter-frame linkage can be inferred from context. Therefore, a pose-guided topology linkage clustering framework is proposed. Our framework consists of three modules: (i) a pose-guided representation module;(ii) a pose-guided embedding module;(iii) a link prediction module. Firstly, the representation coding alone is performed at the level of relational induction bias, embedding the implicit pose structure information in image features. Then, based on the consideration of the topology relationship between adjacent and cross-frame, graph convolutional network is introduced to infer the likelihood of linkage between frame nodes. Experiments show that the method demonstrates excellent scalability in addition to being an effective response to person clustering in case of changes, and does not need the number of clusters as a prior. © 2023 IEEE.

关键词： Convolution

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Human Movement Detection and Gait Periodicity Analysis Using Channel State Information 12

Human Movement Detection and Gait Periodicity Analysis Using...

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12th International Conference on Mobile Ad-Hoc and Sensor Networks, MSN 2016

作者： Liu, Zijuan Wang, Lin Liu, Wenyuan Li, Binbin School of Information Science and Engineering Yanshan University China Key Laboratory for Computer Virtual Technology and System Integration of HeBei Province China School of Economics and Management Yanshan University Qinhuangdao HeBei China

ISBN: (纸本)9781509056965

Under the influence of multipath effects and small scale fading, the robustness and reliability of the existing human detection methods based on radio frequency signals are easy to be impaired. In this paper, we propose a novel design that using the multi-layer filtering of channel state information (CSI) to identify moving targets in dynamic environments and analyze the gait periodicity of human. We employ an efficient CSI subcarrier feature difference to the multi-layer filtering method leveraging principal component analysis (PCA) and discrete wavelet transform (DWT) to eliminate the noises. Furthermore, we propose a profile matching mechanism for human detection and a periodicity analysis mechanism for human gait taking advantage of the above design. We evaluated it with the commodity Wi-Fi infrastructures in different environments. Experimental results indicate that our approach performs identification of human with an average accuracy of 94%. © 2016 IEEE.

关键词： Principal component analysis

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Robust visual tracking via combinative deep learning

Robust visual tracking via combinative deep learning

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International Conference on Mechanical, Electric and Industrial Engineering, MEIE 2018

作者： Wen, Jia Zhao, Jiwei Liu, Pengfei Wang, Hongjun Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Yanshan University Qinhuangdao China Information Science and Engineering College Yanshan University Qinhuangdao China State Key Laboratory of Software Engineering of Hebei Province Yanshan University Qinhuangdao China

Object tracking is a hot topic in computer vision. In recent years, a large number of trackers has been proposed, in which the deep learning tracker has achieved excellent performance. The real-time capability of the deep learning tracker is not good enough due to the high-complexity of the network structures. This paper proposed an innovative tracking method to solve this problem. There are three important differences between this tracker and the other deep learning trackers. Firstly, the overcomplete basis in the deep learning tracker results in heavy computational cost. In order to reduce the complexity of the network, fewer units are used in the first hidden layer to replace the overcomplete basis. Secondly, a training method combining two observation models is used in the tracking process. The denoising automatic encoder is used in the first layer and the backpropagation is used in the other layers. This can avoid the diffusion of gradients which is caused by BP and adapt to the change of the targets easier. Thirdly, this tracker using adaptive particle filter to track targets. The number of particles is dynamic changes in tracking process. In this paper, we use different kinds of unlabelled datum to train network and initialize observation model. The observation model uses the samples collected in the tracking to adjust dynamically so as to adapt to the target appearance and complex environment. Compared with the existing methods, the results of experiments in different video sequences show that this tracker has a higher speed and the similar accuracy compared. © Published under licence by IOP Publishing Ltd.

关键词： Deep learning

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