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2013 International Conference on Information Engineering, ICIE 2013

作者： Chen, Jianmin Yang, Lin Zhang, Honghao Liu, Yan College of Computer Science Beijing University of Technology Beijing China Tianjin Key Lab of Intelligent Computing and Novel Software Technology Tianjin University of Technology Tianjin China National Computer Virus Emergency Response Center Tianjin China

ISBN: (纸本)9781845648558

In order to deal with serious security threats of SQL injection to Web applications, this paper proposes a novel SQL-injection detection method based on genetic algorithm (GA). A unified description for characteristics of SQL-injection was issued by regular expression, and an optimized SQL-injection sequence motherboard was got through GA. We detected harmful levels of SQL-injection attacks using template matching and achieved optimized correction scheme of the algorithm by a large amount of data. © 2014 WIT Press.

关键词： Genetic algorithms

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A clustering algorithm use SOM and K-Means in Intrusion Detection

A clustering algorithm use SOM and K-Means in Intrusion Dete...

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International Conference on E-Business and E-Government (ICEE)

作者： Wang, Huai-Bin Yang, Hong-Liang Xu, Zhi-Jian Yuan, Zheng Tianjin Key Lab. of Intelligent Computing and Novel Software Technology Tianjin University of Technology 300191 Tianjin China Key Laboratory of Computer Vision and System Ministry of Education 300191 Tianjin China Key Laboratory of Computer Vision and System Ministry of Education China

ISBN: (纸本)9780769539973

Improving detection definition is a pivotal problem for intrusion detection. Many intelligent algorithms were used to improve the detection rate and reduce the false rate. Traditional SOM cannot provide the precise clustering results to us, while traditional K-Means depends on the initial value serious and it is difficult to find the center of cluster easily. Therefore, in this paper we introduce a new algorithm, first, we use SOM gained roughly clusters and center of clusters, then, using K-Means refine the clustering in the SOM stage. At last of this paper we take KDD CUP-99 dataset to test the performance of the new algorithm. The new algorithm overcomes the defects of traditional algorithms effectively. Experimental results show that the new algorithm has a good stability of efficiency and clustering accuracy. © 2010 IEEE.

关键词： Self organizing maps

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Identifying high-impact sub-structures for convolution kernels in document-level sentiment classification

Identifying high-impact sub-structures for convolution kerne...

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50th Annual Meeting of the Association for Computational Linguistics, ACL 2012

作者： Tu, Zhaopeng He, Yifan Foster, Jennifer Van Genabith, Josef Liu, Qun Lin, Shouxun Key Lab. of Intelligent Info. Processing Institute of Computing Technology CAS China Computer Science Department New York University United States School of Computing Dublin City University Ireland

ISBN: (纸本)9781937284251

Convolution kernels support the modeling of complex syntactic information in machinelearning tasks. However, such models are highly sensitive to the type and size of syntactic structure used. It is therefore an important challenge to automatically identify high impact sub-structures relevant to a given task. In this paper we present a systematic study investigating (combinations of) sequence and convolution kernels using different types of substructures in document-level sentiment classification. We show that minimal sub-structures extracted from constituency and dependency trees guided by a polarity lexicon show 1.45 point absolute improvement in accuracy over a bag-of-words classifier on a widely used sentiment corpus. © 2012 Association for Computational Linguistics.

关键词： Convolution

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A new algorithm of service discovery based on DHT for mobile application

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Journal of Networks 2011年第10期6卷 1466-1474页

作者： Zhang, De-gan Hu, Yu-xia Wang, Dong Liang, Yan-pin Tianjin Key Lab of Intelligent Computing and Novel software Technology Tianjin University of Technology China Ministry of Education China

In order to solve how to enhance the discovery efficiency and coverage, based on DHT (Distributed Hash Table) and Small World Theory, we put forward a new algorithm of service discovery for mobile application. In traditional DHT discovery algorithm, each node maintains the finger-table that store node information of adjacent node. By using Small-World Theory, we put forward adding a remote node into the finger-table and adding the corresponding remote index. It is different from selecting the remote connection node randomly. We select the remote connection node by calculating local node and it can assure not only the cove range of service discovery but also not increase the length of finger-table, which simplifies the calculation of the finger-table and maintenance work. The simulation proved that the algorithm can reduce the path length of service discovery effectively, improve success rate of service discovery. © 2011 Academy Publisher.

关键词： Mobile computing

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A kind of new web-based method of seamless migration

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International Journal of Advancements in computing technology 2011年第5期3卷 32-40页

作者： Zhang, De-gan Dai, Wen-bo Kang, Xue-jing Wang, Dong Tianjin Key Lab of Intelligent Computing and Novel software Technology Tianjin University of Technology China Ministry of Education China

To improve the mobile applications under the banner of the Internet of Things, we propose and design a new kind of Web-based method of seamless migration. The method can ensure the media seamless migration fast, smoothly and correctly. Implemented method will better solve the migration of media on the application layer of mobile application. Tests have shown our suggested seamless migration strategies are effective. This method will serve universal Web-based mobile application.

关键词： Websites

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Joint Deep Matching Model of OCT Retinal Layer Segmentation

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Computers, Materials & Continua 2020年第6期63卷 1485-1498页

作者： Mei Yang Yuanjie Zheng Weikuan Jia Yunlong He Tongtong Che Jinyu Cong School of Information Science and Engineering at Shandong Normal University Jinan250358China Key Lab of Intelligent Computing and Information Security in Universities of Shandong Shandong Provincial Key Laboratory for Novel Distributed Computer Software TechnologyInstitute of Biomedical SciencesShandong Normal UniversityJinan250358China INSA Lyon University of LyonCNRSInsermVilleurbanne69621 CedexFrance

Optical Coherence Tomography(OCT)is very important in medicine and provide useful diagnostic *** retinal layer thicknesses plays a vital role in pathophysiologic factors of many ocular *** the existing retinal layer segmentation approaches,learning or deep learning-based methods belong to the ***,most of these techniques rely on manual-marked layers and the performances are limited due to the image *** order to overcome this limitation,we build a framework based on gray value curve matching,which uses depth learning to match the curve for semi-automatic segmentation of retinal layers from *** depth convolution network learns the column correspondence in the OCT image *** whole OCT image participates in the depth convolution neural network operation,compares the gray value of each column,and matches the gray value sequence of the transformation column and the next *** this algorithm,when a boundary point is manually specified,we can accurately segment the boundary between retinal *** experimental results obtained from a 54-subjects database of both normal healthy eyes and affected eyes demonstrate the superior performances of our approach.

关键词： OCT retinal segmentation deep learning 1D convolution

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Semi-supervised classification method of SAR images using spectral clustering in contourlet domain 4

Semi-supervised classification method of SAR images using sp...

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2019 4th International Seminar on Computer technology, Mechanical and Electrical Engineering, ISCME 2019

作者： Jiang, Kaiwen Zhang, Degan Xu, Haixia Key Laboratory of Computer Vision and System Tianjin University of Technology Ministry of Education 300384 China Tianjin Key Lab of Intelligent Computing and Novel Software Technology Tianjin University of Technology Tianjin China School of Electronic and Information Engineering Tianjin Vocational Institute Tianjin300410 China

A new based on Semi-supervised classification theory for SAR images in contourlet domain is proposed, in this paper. Attempting to get better and faster performance, the PSO algorithm (Particle swarm optimization algorithm) and contourlet domain is proposed to instead of traditional k-means algorithm. PSO is used to find the global optimum by performing a global search in the whole solution space. And then, contourlet is applied in front of construct the similarity matrix to extract more effective eigenvalues. In section five, the proposed algorithm got better classification results than the traditional k-means algorithm which is proved by experimental results show that in terms of running time, classification accuracy and Kappa coefficient. © Published under licence by IOP Publishing Ltd.

关键词： Synthetic aperture radar

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A Kind of new parallax algorithm based on symmetric continuous optimization 5

A Kind of new parallax algorithm based on symmetric continuo...

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2020 5th International Seminar on Computer technology, Mechanical and Electrical Engineering, ISCME 2020

With the fast development of 3D imaginations becomes more and more fascination, multi-view stereo based 3D reconstruction is a significant technique for those application. To facilitate the subsequent processing of 3D reconstruction and reduce the possibility of other algorithms falling into local optimal solutions, attempting to get better and faster performance, a new parallax calculation based on symmetric continuous optimization is proposed in this paper. The algorithm is proposed here will be tested respectively in the same data, in order to certificate the algorithm applied is better than traditional minimize El algorithm. © Published under licence by IOP Publishing Ltd.

关键词： Optimization

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DNS Covert Channel Attack Detection Based on Spatio-Temporal Feature Fusion 22

DNS Covert Channel Attack Detection Based on Spatio-Temporal...

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22nd IEEE International Symposium on Parallel and Distributed Processing with Applications, ISPA 2024

作者： You, Wei Zhao, Chunlei Shan, Chao Dong, Guozhong Yu, Jie Guan, Yong Tianjin University of Technology Tianjin Key Laboratory of Intelligent Computing and Software New Technology Tianjin China Coordination Center of China Hubei Branch of National Computer Network Emergency Response Technical Team HuBei China Pengcheng Laboratory Department of New Networks Shenzhen China

ISBN: (纸本)9798331509712

An increasing number of Advanced Persistent Threat (APT) organizations are utilizing DNS (Domain Name System) covert channels to evade network intrusion detection systems and establish private authoritative servers for remote attacks. However, current detection models for DNS covert channels often have poor performance and limited generalization ability. To address these challenges, we propose a DNS covert channel attack detection method based on spatiotemporal feature fusion. This method combines the Interaction timing sequence features of DNS traffic with the spatial statistical features of domain names, and constructs a detection model called ConvSLSTM, which integrates a Convolutional Neural Network (CNN) with a stacked Long Short Term Memory (LSTM) network. CNN extracts local spatial features from traffic, while stacked LSTM captures Interaction timing sequence features, significantly improving detection accuracy. This article uses three typical public datasets for experiments, which contain a total of 440000 DNS covert channel attack data. Comparative experiments show that our method is significantly superior to existing methods and exhibits stronger generalization ability in detecting DNS covert channel attacks constructed by unknown tools. © 2024 IEEE.

关键词： Network intrusion

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Hessian based image structure adaptive gradient vector flow for parametric active contours

Hessian based image structure adaptive gradient vector flow ...

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2010 17th IEEE International Conference on Image Processing, ICIP 2010

作者： Wang, Y.Q. Chen, W.F. Yu, T.L. Zhang, Y.T. Tianjin Key Lab. of Intelligent Computing and Novel Software Technology Tianjin University of Technology Tianjin 300191 China Key Lab. of Image Processing Southern Medical University Guangzhou 510515 China Dept. of Radiology General Hospital Tianjin Medical University Tianjin 300052 China

ISBN: (纸本)9781424479948

Active contours have been one of the most successful methods for image segmentation during the last two decades, but one of the shortcomings of being unable to converge to concavity is a handicap to its effectiveness. In order to address this issue, the gradient vector flow (GVF) was put forth. Although there have been a great number of works on GVF, the image structure has seldom been incorporated into GVF algorithm. In this work, the image structure characterized by the Hessian matrix is incorporated into the GVF algorithm by reformulating the smoothness constraint of GVF into matrix form. In this way, the associated diffusion PDEs are anisotropic and the modified GVF snake can converge to very long concavity and preserve weak edge simultaneously. Experiments and comparisons are presented to demonstrate the properties of the proposed strategies. © 2010 IEEE.

关键词： Image segmentation

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