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ENHANCED AUTOMATED INTRUSION PREVENTION IN NETWORK SECURITY

ENHANCED AUTOMATED INTRUSION PREVENTION IN NETWORK SECURITY

2010 2nd International Conference on computer Engineering and Technology(2010年第二届计算机工程与技术国际会议 ICCET 2010)

作者： Xiao Dong He Teck Chaw Ling Department of Data Communication and Engineering Guangzhou Civil Aviation College Guangzhou City Gua Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur Malaysia

ISBN: (纸本)9781424463473

An automated Intrusion Prevention Mechanism (AIPM) which comprises the functionalities of IDS,IPS,and auto configuring network devices is proposed to enhance network security. AIPM is a mechanism that includes automated intrusion prevention function and automated analysis of intrusion messages function. In addition,the ability of automatically detecting and analyzing network traffic allows AIPM to detect malicious attacks in almost real time. Likewise,the ability of automatically analyzing intrusion messages and network configuration enable AIPM to build a topological view and locate the source of a malicious attack. Results from the case studies show that AIPM imposes lower overhead than conventional method,which queries all pre-defined routers to block every interface irrespective of where the attack is launched. In summary,AIPM which incorporates the functionalities of IDS/IPS offers network protection against potential malicious acts without incurring additional overheads as compare to the conventional method.

关键词： Network:Security:IDS:IPS:Intrusion

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Comparative study of Goal-Oriented Requirements Engineering

Comparative study of Goal-Oriented Requirements Engineering

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International Conference on New Trends in Information and Service science, NISS

作者： Naeem Ur Rehman Sarfraz Bibi Sohail Asghar Simon Fong Center of Research in Data Engineering Mohammad Ali Jinnah University Islamabad Pakistan Department of Computer Sciences SZABIST Islamabad Pakistan Faculty of Science and Technology University of Macau Macao China

ISBN: (纸本)9781424469826;9788988678183

Requirements Engineering is a sub discipline of Software Engineering, which is an important and vital phase in the overall software engineering life cycle. Software as a final product is deemed to fail if it does not fulfill the needs of its users. A number of contributions have been made to refine the requirements engineering process. Most of them attempted to link requirements to goals. This new trend is called as Goal-Oriented Requirement Engineering (GORE). A number of goal-oriented RE methods have been subsequently derived by various researches. This paper reviews some of the significant research works done in GORE. The comparative study may serve as a guide for readers to select an appropriate goal-oriented technique for fulfilling his/her requirements engineering needs.

关键词： data engineering Software engineering Electronic government Project management Sociotechnical systems Risk management Design engineering computer architecture Programming

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Vehicle and driver scheduling modelling: A case study in UKM

Vehicle and driver scheduling modelling: A case study in UKM

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2009 2nd Conference on data Mining and Optimization, DMO 2009

作者： Oughalime, Ahmed Ismail, Wan Rosmanira Liong, Choong-Yeun Ayob, Masri School of Mathematical Sciences Faculty of Science and Technology Malaysia Data Mining and Optimisation Research Group Department of Computer Science Faculty of Information Science and Technology Malaysia

ISBN: (纸本)9781424449446

This paper deals with the vehicle and driver scheduling problems at UKM transportation department. Given daily sets of trips, drivers and non homogenous vehicles fleet, the aim is to schedule the resources in order to cover, if possible, all the trip demands. The problem formulation has been done using sequential approach where an integer programming and goal programming models have been presented respectively for vehicle scheduling problem and driver scheduling problem. © 2009 IEEE.

关键词： Integer programming

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A hybrid approach for learning concept hierarchy from malay text using GAHC and immune network

A hybrid approach for learning concept hierarchy from malay ...

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8th International Conference on Artificial Immune Systems, ICARIS 2009

作者： Nazri, Mohd Zakree Ahmad Shamsuddin, Siti Mariyam Bakar, Azuraliza Abu Abdullah, Salwani Data Mining and Optimization Research Group Faculty of Information Science and Technology Universiti Kebangsaan Malaysia Bangi Selangor 43650 Malaysia Soft Computing Research Group Faculty of Computer Science and Information System Universiti Teknologi Malaysia Skudai Johor 81100 Malaysia

ISBN: (纸本)3642032451

The human immune system provides inspiration in the attempt of solving the knowledge acquisition bottleneck in developing ontology for semantic web application. In this paper, we proposed an extension to the Guided Agglomerative Hierarchical Clustering (GAHC) method that uses an Artificial Immune Network (AIN) algorithm to improve the process of automatically building and expanding the concept hierarchy. A small collection of Malay text is used from three different domains which are IT, Biochemistry and Fiqh to test the effectiveness of the proposed approach and also by comparing it with GAHC. The proposed approach consists of three stages: pre-processing, concept hierarchy induction using GAHC and concept hierarchy learning using AIN. To validate our approach, the automatically learned concept hierarchy is compared to a reference ontology developed by human experts. Thus it can be concluded that the proposed approach has greater ability to be used in learning concept hierarchy. © 2009 Springer.

关键词： Ontology

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Building a new taxonomy for data discretization techniques

Building a new taxonomy for data discretization techniques

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2009 2nd Conference on data Mining and Optimization, DMO 2009

作者： Bakar, Azuraliza Abu Othman, Zulaiha Ali Shuib, Nor Liyana Mohd Data Mining and Optimization Research Group Center of Artificial Intelligence Technology University Kebangsaan Malaysia 43600 UKM Bangi Selangor Malaysia Faculty of Computer Science and Information Technology University Malaya Malaysia

ISBN: (纸本)9781424449446

data preprocessing is an important step in data mining. It is used to resolve various types of problem in a large dataset in order to produce quality data. It consists of four steps, namely, data cleaning, integration, reduction and transformation. The literature shows that each preprocessing step consists of various techniques. In order to develop quality data, a data miner must decide the most appropriate techniques in every step of data preprocessing. In this study, we focus on data reduction particularly data discretization as one important data preprocessing step. data reduction involves reducing the data distribution by reducing the range of continuous data into a range of values or categories. data discretization plays a major role in reducing the attribute intervals of data values. Finding an appropriate number of discrete values will improve the performance of the data mining modelling, particularly in terms of classification accuracy. This paper proposes four levels of data discretization taxonomy as follows: hierarchical and non-hierarchical;splitting, merging and combination;supervised and unsupervised combinations;and binning, statistic, entropy and other related techniques. The taxonomy is developed based on a detailed review of previous discretization techniques. More than fifty techniques are investigated, and the structure of the discretization approach is outlined. Guidelines on how to use the proposed taxonomy are also discussed. © 2009 IEEE.

关键词： data mining

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Vehicle and driver scheduling modelling: A case study in UKM

Vehicle and driver scheduling modelling: A case study in UKM

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Conference on data Mining and Optimization, DMO

作者： Ahmed Oughalime Wan Rosmanira Ismail Choong-Yeun Liong Masri Ayob School of Mathematical Sciences Faculty of Science and Technology Universiti Kebangsaan Malaysia Malaysia Data Mining and Optimisation Research Group Department of Computer Science Faculty of Information Science and Technology Universiti Kebangsaan Malaysia Malaysia

关键词： Vehicle driving Processor scheduling Transportation Linear programming Costs Vehicles data mining Paper technology Mathematical model computer science

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Building a new taxonomy for data discretization techniques

Building a new taxonomy for data discretization techniques

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Conference on data Mining and Optimization, DMO

作者： Azuraliza Abu Bakar Zulaiha Ali Othman Nor Liyana Mohd Shuib Data Mining & Optimization Research Group University Kebangsaan Malaysia Bangi Selangor Malaysia Faculty of Computer Science and Information Technology University Malaya MALAYSIA

data preprocessing is an important step in data mining. It is used to resolve various types of problem in a large dataset in order to produce quality data. It consists of four steps, namely, data cleaning, integration, reduction and transformation. The literature shows that each preprocessing step consists of various techniques. In order to develop quality data, a data miner must decide the most appropriate techniques in every step of data preprocessing. In this study, we focus on data reduction particularly data discretization as one important data preprocessing step. data reduction involves reducing the data distribution by reducing the range of continuous data into a range of values or categories. data discretization plays a major role in reducing the attribute intervals of data values. Finding an appropriate number of discrete values will improve the performance of the data mining modelling, particularly in terms of classification accuracy. This paper proposes four levels of data discretization taxonomy as follows: hierarchical and non-hierarchical; splitting, merging and combination; supervised and unsupervised combinations; and binning, statistic, entropy and other related techniques. The taxonomy is developed based on a detailed review of previous discretization techniques. More than fifty techniques are investigated, and the structure of the discretization approach is outlined. Guidelines on how to use the proposed taxonomy are also discussed.

关键词： Taxonomy data preprocessing data mining Cleaning Artificial intelligence computer science Information technology Merging Statistics Entropy

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Lecture Notes in Business Information Processing: Preface

Lecture Notes in Business Information Processing

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Lecture Notes in Business Information Processing 2009年 32 LNBIP卷 XVI页

作者： Bomarius, Frank Oivo, Markku Jaring, Päivi Abrahamsson, Pekka University of Ljubljana Faculty of Computer and Information Science Laboratory for Data Technologies Ljubljana Slovenia Alpen Adria Universität Klagenfurt Institut für Informatik-Systeme Klagenfurt Austria

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Acquisition, analysis and distribution of real-time multi-sensor satellite data, in a high performance computing environment, for disaster mitigation applications: Case studies from the NATO science for peace funded kamal ewida earth observatory in Egypt, the electronic Geophysical Year (eGY)-Africa and the US Geological Survey supported AmericaView

Acquisition, analysis and distribution of real-time multi-se...

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IEEE Sensors 2009 Conference - SENSORS 2009

作者： Rochon, Gilbert L. Araya, Bereket Biehl, Larry L. Grant, Darion Ersoy, Okan Quansah, Joseph Altay, Gülay Wahab, M. Magdy Abdel El Afandi, Gamal Salah El Ghazawi, Tarek Mohamed, Mohamed A. Shokr, Mohammed Sithole, Happy Purdue Terrestrial Observatory Purdue University ITaP/RCAC West Lafayette IN United States School of Electrical and Computer Engineering Purdue University West Lafayette IN United States Department of Agricultural and Biological Engineering Purdue University W. Lafayette IN United States Kandilli Observatory and Earthquake Research Institute Boǧaziçi University Istanbul Turkey Dept. of Meteorology and Astronomy Faculty of Science Cairo University Giza Cairo Egypt Dept. of Astronomy and Meteorology Faculty of Science Al Azhar University Nasr City Cairo Egypt Dept. of Electrical and Computer Engineering George Washington University Washington DC United States N'Djamena Chad Environment Canada Data Assimilation and Satellite Meteorology Research Toronto ON Canada Rosebank Cape Town South Africa

ISBN: (纸本)9781424445486

The paper presents an implementation of the current state-of-the-art, with respect to acquisition, analysis and distribution of real-time remotely sensed data from multiple polar orbiting and geostationary earth observing satellite sensors, deploying high performance computing for time-critical disaster mitigation applications. The authors also describe the prototype Kamal Ewida Earth Observatory (KEEO), now under development at Cairo University & at Al Azhar University in Egypt, as a technological exemplar of indigenous expertise, real-time remote sensing, near-real-time spatial data products, supercomputer access from Egypt's space agency-NARSS, partnerships with multi-lateral agencies (e.g. UN WHO, Electronic Geophysical Year (eGY)-Africa), sensor data archives from the United States Geological Survey (USGS)-supported AmericaView, funding from NATO's science for Peace Program and collaborative research with Boǧaziçi University's Kandilli Observatory and Earthquake Research Institute (KOERI) in Istanbul, Turkey and with Purdue University's Rosen Center for Advanced Computing's Purdue Terrestrial Observatory (PTO) in West Lafayette, Indiana, USA. ©2009 IEEE.

关键词： Remote sensing

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Image fusion based on principal component analysis and high-pass filter

Image fusion based on principal component analysis and high-...

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International Conference on computer Engineering and Systems

作者： Mohamed R. Metwalli Ayman H. Nasr Osama S. Farag Allah S. El-Rabaie Data Reception Analysis and Receiving Station Affairs Division National Authority for Remote Sensing and Space Sciences Cairo Egypt Department of Computer science and Engineering Faculty of Electronic Engineering Menoufia University Menoufia Egypt Department of Electronics and Electrical Communications Faculty of Electronic Engineering Menoufia University Menoufia Egypt

ISBN: (纸本)9781424458424

Several commercial earth observation satellites carry dual-resolution sensors, which provide high spatial resolution panchromatic image and low spatial resolution multi-spectral image. Image fusion techniques are therefore useful for integrating a high spectral resolution image with a high spatial resolution image, to produce a fused image with high spectral and spatial resolutions. Some image fusion methods such as IHS, PC and BT provide superior visual high-resolution multi-spectral images but ignore the requirement of high-quality synthesis of spectral information. The high-quality synthesis of spectral information is very important for most remote sensing application based on spectral signatures, such as lithology, soil and vegetation analysis. Another family of image fusion techniques such as HPF operates on the basis of the injection of high-frequency components from the high spatial resolution panchromatic image into the multi-spectral image. This family of methods provides less spectral distortion. In this paper we propose to integrate between the two families PCA and HPF to provide pan sharpened image with superior spatial resolution and less spectral distortion. The experiments have shown that the proposed fusion method retains the spectral characteristics of the multi-spectral image and improves at the same time the spatial resolution of the fused image.

关键词： Image fusion Principal component analysis Spatial resolution Multispectral imaging Filters Artificial satellites Image sensors Image resolution Remote sensing Soil

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