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2008 International Conference on Computational Intelligence and Security最新文献

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Information Management System of Automobile Chassis Dynamometer Based on Multi Agent Web Serve 基于多代理Web服务的汽车底盘测功机信息管理系统
2008 International Conference on Computational Intelligence and Security Pub Date : 2008-12-13 DOI: 10.1109/CIS.2008.140
Long Guo, Hongli Wang
{"title":"Information Management System of Automobile Chassis Dynamometer Based on Multi Agent Web Serve","authors":"Long Guo, Hongli Wang","doi":"10.1109/CIS.2008.140","DOIUrl":"https://doi.org/10.1109/CIS.2008.140","url":null,"abstract":"In the process of endurance road testing and simulated road test, dispatchers' scheduling was experiential and blindfold in some degree and static scheduling restricted the continuity of the construction. Serious problems such as labour holdup, material awaiting and scheduling delay could occur when the old scheduling technique was used. This paper presents management structure based on Multi-agent system(MAS) that has the abilities of intelligent modelling and dynamic scheduling. MAS model deals with single agent's communication and corresponding in distributed automobile chassis dynamometer firstly, next we apply intelligent algorithm, such as information alternation and principal component analysis (PCA), to solve dynamic scheduling in the plant. Intelligent algorithm can optimize the match of agents and make the system dynamic balance. At last, Information management system of automobile chassis dynamometer based on multi agent Web serve and was realized. resource become economy, the efficiency are raised. It is advantage to overcome the influence from subjective error.","PeriodicalId":255247,"journal":{"name":"2008 International Conference on Computational Intelligence and Security","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130652365","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
An Improved Approach to Access Graph Generation 一种改进的访问图生成方法
2008 International Conference on Computational Intelligence and Security Pub Date : 2008-12-13 DOI: 10.1109/CIS.2008.68
Xiaochun Xiao, Tiange Zhang, Gendu Zhang
{"title":"An Improved Approach to Access Graph Generation","authors":"Xiaochun Xiao, Tiange Zhang, Gendu Zhang","doi":"10.1109/CIS.2008.68","DOIUrl":"https://doi.org/10.1109/CIS.2008.68","url":null,"abstract":"In order to assess the security of network information system, many graph-based approaches have been proposed. Attack Graph is the most influential one. But attack graphs grow exponentially with the size of the network. In this paper, we propose an improved access graph based model to analyze network security. As a complement to the attack graph approach, the access graph is host-centric approach, which grows polynomially with the number of hosts and so has the benefit of being computationally feasible on large networks. Compared with the related works, our approach improves in both performance and computational cost.","PeriodicalId":255247,"journal":{"name":"2008 International Conference on Computational Intelligence and Security","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123197549","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Application of Data Warehouse Technology in Data Center Design 数据仓库技术在数据中心设计中的应用
2008 International Conference on Computational Intelligence and Security Pub Date : 2008-12-13 DOI: 10.1109/CIS.2008.124
Xuanzi Hu, Kuanfu Wang
{"title":"Application of Data Warehouse Technology in Data Center Design","authors":"Xuanzi Hu, Kuanfu Wang","doi":"10.1109/CIS.2008.124","DOIUrl":"https://doi.org/10.1109/CIS.2008.124","url":null,"abstract":"Chinese electronic government (E-Government) has achieved great success in several years, to quicken the pace of building E-Government, the central government of China has programmed to establish four governance information resource databases in next five years, data center construction in the developed cities is becoming an important project for present China¿s E-Government. Through investigation and analysis requirements of Nanhai city for data and business, this paper presents the architecture of data center, which is composed of six main components: data share and exchange platform, kernel database, support application platform, application database, data center management platform, and data center security platform. Extensible markup language (XML) and data warehouse technology are adopted for data center. Proposed method has already been successfully used in data center of Nanhai city, which is listed as the pilot cities for Model Project of China's E-government application.","PeriodicalId":255247,"journal":{"name":"2008 International Conference on Computational Intelligence and Security","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114319068","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 7
Discrete Fourier Transform Computation Using Neural Networks 离散傅里叶变换的神经网络计算
2008 International Conference on Computational Intelligence and Security Pub Date : 2008-12-13 DOI: 10.1109/CIS.2008.36
R. Velik
{"title":"Discrete Fourier Transform Computation Using Neural Networks","authors":"R. Velik","doi":"10.1109/CIS.2008.36","DOIUrl":"https://doi.org/10.1109/CIS.2008.36","url":null,"abstract":"In this paper, a method is introduced how to process the Discrete Fourier Transform (DFT) by a single-layer neural network with a linear transfer function. By implementing the suggested solution into neuro- hardware, advantage can be taken of actual parallel processing of spectral components of different frequencies and of different coefficients of each spectral line. When computing the DFT due to input data pre-processing for a certain neural network solution, a stand alone solution of neural networks without the necessity of additional computational resources can be achieved.","PeriodicalId":255247,"journal":{"name":"2008 International Conference on Computational Intelligence and Security","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124232793","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 27
Curve Forecast Based on BP Neural Networks with Application of Mental Curve Tracing 基于BP神经网络的曲线预测与心理曲线跟踪的应用
2008 International Conference on Computational Intelligence and Security Pub Date : 2008-12-13 DOI: 10.1109/CIS.2008.164
Chuanmei Wang, Hengqing Tong
{"title":"Curve Forecast Based on BP Neural Networks with Application of Mental Curve Tracing","authors":"Chuanmei Wang, Hengqing Tong","doi":"10.1109/CIS.2008.164","DOIUrl":"https://doi.org/10.1109/CIS.2008.164","url":null,"abstract":"Each curve belongs to a multivariate nonparametric regression model, and many shape-invariant curves form a curve family connected with a reference curve by some parameters. Curve drift models can be built to forecast many curves in practice. In this paper, we put forward the multivariate nonparametric regression mental curve drift model after our study of the mental curves of visual scenes composing. However, the multivariate nonparametric regression mental curve drift model is very complicated to trace. And we apply neural networks to solve this problem. Neural networks have been shown to be particularly effective in handling some complexities commonly found in complicated regression models and datum. Here, we apply neural networks to fit the curves family and to forecast the mental curves with curve drift. An example is provided to show the feasibility of curve drift and mental curve tracing with neural networks.","PeriodicalId":255247,"journal":{"name":"2008 International Conference on Computational Intelligence and Security","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126468741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Performance Comparison of Nonlinear Dimensionality Reduction Methods for Image Data Using Different Distance Measures 不同距离下图像数据非线性降维方法的性能比较
2008 International Conference on Computational Intelligence and Security Pub Date : 2008-12-13 DOI: 10.1109/CIS.2008.18
M. Naseer, S. Qin
{"title":"Performance Comparison of Nonlinear Dimensionality Reduction Methods for Image Data Using Different Distance Measures","authors":"M. Naseer, S. Qin","doi":"10.1109/CIS.2008.18","DOIUrl":"https://doi.org/10.1109/CIS.2008.18","url":null,"abstract":"During recent years a special class of nonlinear dimensionality reduction (NLDR) methods known as manifold learning methods, obtain a lot of attention for low dimension representation of high dimensional data. Most commonly used NLDR methods like Isomap, locally linear embedding, local tangent space alignment, Hessian locally linear embedding, Laplacian eigenmaps and diffusion maps, construct their logic on finding neighborhood points of every data point in high dimension space. These algorithms use Euclidean distance as measurement metric for distance between two data points. In literature different (dis)similarity measures are available for measuring distances between two data points/images. In this paper the authors made a systematic comparative analysis for performance of different NLDR algorithms in reducing high dimensional image data into a low dimensional 2D data using different distance measures. The performance of an algorithm is measured by the fact that how successfully it preserves intrinsic geometry of high dimensional manifold. Visualization of low dimensional data reveals the original structure of high dimensional data.","PeriodicalId":255247,"journal":{"name":"2008 International Conference on Computational Intelligence and Security","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126426904","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 7
An New Algorithm of Association Rule Mining 一种新的关联规则挖掘算法
2008 International Conference on Computational Intelligence and Security Pub Date : 2008-12-13 DOI: 10.1109/CIS.2008.42
Jun Gao
{"title":"An New Algorithm of Association Rule Mining","authors":"Jun Gao","doi":"10.1109/CIS.2008.42","DOIUrl":"https://doi.org/10.1109/CIS.2008.42","url":null,"abstract":"Efficiency is critical to data mining algorithm. Based on fully analyzing the PF_growth, an association rule mining algorithm, we in this paper give a new association rule mining algorithm called MFP. MFP algorithm converts a transaction database to an MFP_tree through scanning the transaction database only once, then prune the tree and at last mine the tree. Because the MFP algorithm scans a transaction database one time less than the FP_growth algorithm, the MFP algorithm is more efficient under certain conditions.","PeriodicalId":255247,"journal":{"name":"2008 International Conference on Computational Intelligence and Security","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125462648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Towards an Adaptive Intrusion Detection System: A Critical and Comparative Study 迈向自适应入侵检测系统:关键与比较研究
2008 International Conference on Computational Intelligence and Security Pub Date : 2008-12-13 DOI: 10.1109/CIS.2008.94
Hassina Bensefia, M. Ahmed-Nacer
{"title":"Towards an Adaptive Intrusion Detection System: A Critical and Comparative Study","authors":"Hassina Bensefia, M. Ahmed-Nacer","doi":"10.1109/CIS.2008.94","DOIUrl":"https://doi.org/10.1109/CIS.2008.94","url":null,"abstract":"An intrusion detection system (IDS) that is destined to supervise an environment, must adjust itself according to every change in the environment and be handling every new attack occurrence. This feature is referred to as the adaptability. It makes the IDS a learning system in relation to its target environment, practicing an autonomous and continuous learning of new attacks. This paper develops a critical and comparative study of existing adaptive intrusion detection models. The objective of such study is to be oriented with regard to related works in the aim of building our own vision to add contribution in the IDS adaptability context.","PeriodicalId":255247,"journal":{"name":"2008 International Conference on Computational Intelligence and Security","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132191853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
A Novel Multi-Objective Evolutionary Algorithm Based on External Dominated Clustering 一种新的基于外部支配聚类的多目标进化算法
2008 International Conference on Computational Intelligence and Security Pub Date : 2008-12-13 DOI: 10.1109/CIS.2008.186
Lei Fan, Yuping Wang
{"title":"A Novel Multi-Objective Evolutionary Algorithm Based on External Dominated Clustering","authors":"Lei Fan, Yuping Wang","doi":"10.1109/CIS.2008.186","DOIUrl":"https://doi.org/10.1109/CIS.2008.186","url":null,"abstract":"Evolutionary algorithms (EAs) have wide applications in practice and many advantages over traditional methods in solving nonlinear and complex optimal problems. In this paper, we propose a novel clustering technique, in which the infeasible solutions are employed to divide the feasible solutions into several clusters. There is no more one infeasible individual in each cluster. A novel evolutionary algorithm based on this technique called ED-MOEA is proposed for dealing with constrained multi-objective problems. Simulation results on five test problems indicate the proposed algorithm is effective.","PeriodicalId":255247,"journal":{"name":"2008 International Conference on Computational Intelligence and Security","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132423801","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Optimize Algorithm of Decision Tree Based on Rough Sets Hierarchical Attributes 基于粗糙集层次属性的决策树优化算法
2008 International Conference on Computational Intelligence and Security Pub Date : 2008-12-13 DOI: 10.1109/CIS.2008.89
Yuan Zhang, Yuejin Lv
{"title":"Optimize Algorithm of Decision Tree Based on Rough Sets Hierarchical Attributes","authors":"Yuan Zhang, Yuejin Lv","doi":"10.1109/CIS.2008.89","DOIUrl":"https://doi.org/10.1109/CIS.2008.89","url":null,"abstract":"Rough set theory is a new mathematical tool to deal with vagueness and uncertainty. And now it has been widely applied in constructing decision tree which has no hierarchical attributes inside. However, hierarchical attributes exist generally in realistic environment, which leads that decision making has max rules. Using max rules to build decision trees can optimize decision trees and has practical values as well. So, in order to deal with hierarchical attributes in decision tree, this paper try to design an optimize algorithm of decision tree based on rough sets hierarchical attributes (ARSHA), which works by combining the hierarchical attribute values and deleting the associated objects when max rules exist in decision table. So that the algorithm developed in this paper can abstract the simplest rule set that can cover all information for decision making. Finally, a real example is used to demonstrate its feasibility and efficiency.","PeriodicalId":255247,"journal":{"name":"2008 International Conference on Computational Intelligence and Security","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133915850","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
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