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International Conference on Advanced Information Management and Service

作者： Farhoud Hosseinpour Kamalrulnizam Abu Bakar Amir Hatami Hardoroudi Ali Farhang Dareshur Faculty of Computer Science and Information System University of Technology Kuala Lumpur Malaysia Advanced Informatics School (AIS) University of Technology Kuala Lumpur Malaysia

Currently Intrusion detection systems have grown to be an ordinary component of network security infrastructure. With mounting global network connectivity, the issue of intrusion has achieved importance, promoting active research on efficient Intrusion Detection systems (IDS). Artificial Immune system (AIS) is a new bio-inspired model which is applied for solving various problems in the field of information security. The unique features AIS encourage the researchers to employ this techniques in variety of applications and especially in intrusion detection systems. Proper IDS design is essential to improve the performance of the IDS. The centralized design of this IDS has disadvantage of central processing for massive processes for each packets passing trough network. In this paper we proposed a distributed multi-layerd framework to enhance the detection performance and efficiency of this IDS. In our design the genetic algorithm is used for enhancing the secondary immune response. The fundamental design of our proposed AIS based IDS consists of 2 main components: IDS central engine and detection sensors. Each of these components is composed of some agents which correlate with each other in order to detect the anomalies and intrusions. Our design goal is to decrease the detection time for each connection by distributing the detectors to each host.

关键词： Detectors Intrusion detection Artificial immune systems Training Engines

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A taxonomy of Botnet detection techniques

A taxonomy of Botnet detection techniques

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International Conference on computer Science and Information technology (CSIT)

作者： Hossein Rouhani Zeidanloo Mohammad Jorjor Zadeh Shooshtari Payam Vahdani Amoli M. Safari Mazdak Zamani Faculty of Computer Science and Information System University of Technology Kuala Lumpur Malaysia Industrial Engineering Department Amirkabir University of Technology슠 Tehran Iran

Among the diverse forms of malware, Botnet is the most widespread and serious threat which occurs commonly in today's cyber attacks. Botnets are collections of compromised computers which are remotely controlled by its originator (BotMaster) under a common Commond-and-Control (C&C) infrastructure. They provide a distributed platform for several illegal activities such as launching distributed denial of service (DDOS) attacks against critical targets, malware distribution, phishing, and click fraud. Most of the existing Botnet detection approaches concentrate only on particular Botnet command and control (C&C) protocols (e.g., IRC, HTTP) and structures (e.g., centralized), and can become ineffective as Botnets change their structure and C&C techniques. The detection of Botnet has been a major research topic in recent years. Different techniques and approaches have been proposed for detection and tracking of Botnet. This survey classifies Botnet detection techniques into two approaches. One approach is based on setting up honeynets and another approach is based on Intrusion Detection system( IDS) which has been categorized into signature-based and anomaly-based detection techniques.

关键词： Monitoring Computational modeling computers Cryptography

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Features Discovery for Web Classification Using Support Vector Machine

Features Discovery for Web Classification Using Support Vect...

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International Conference on Intelligent Computing and Cognitive Informatics (ICICCI)

作者： M.S. Othman L.M. Yusuf J. Salim Faculty of Computer Science and Information System Universiti Teknologi Malaysia Skudai Johor Malaysia Faculty of Information Science and Technology Universiti Kebangsaan Malaysia Bangi Selangor Malaysia

The ever fast-expanding web information resources pose a big challenge to internet users seeking the most relevant, latest and quality information. The sheer vast amount of web information has resulted in restructuring of the resources. Thus, an appropriate web classification method needs to be established in order for quality web information to be accessed. This paper intends to discuss the web document features that classify the web information resources. Six web document features have been identified which are text, meta tag and title (A), title and text (B), title (C), meta tag and title (D), meta tag (E) and text (F). The Support Vector Machine (SVM) method is used to classify the web document while four types of kernels namely: Radial Basis Function (RBF), linear, polynomial and sigmoid kernels was applied to test the accuracy of the classification. The studies show that the text, meta tag and title (A) features is the best features for classification of web document that employs the four kernels followed by the features on title and text (B) as well as the features on meta tag and title (C). The studies also found that the linear kernel is the best kernel in classifying the web document compared to the RBF, polynomial and sigmoid kernel.

关键词： Support vector machines HTML Kernel Accuracy Internet Text categorization Feature extraction

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Web classification using extraction and machine learning techniques

Web classification using extraction and machine learning tec...

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International Symposium on Information technology, ITSim

作者： L. M. Yusuf M. S. Othman J. Salim Faculty of Computer Science and Information System Universiti Teknologi Malaysia Skudai Johor Malaysia Faculty of Information Science and Technology Universiti Kebangsaan Malaysia Bangi Selangor Malaysia

Internet services that has become easier to access has contributed to the drastic increase in the number of web pages. This phenomenon has created new difficulties to internet users about retrieving the latest, relevant and excellent web information. This is due to the enormous contents of web information that have caused problems in the restructuring of web information. Thus, in order to ensure the latest, quality and relevant web information is optimally retrievable, it is necessary to undertake the task of web document classification. This paper discusses the result of classifying web document using the extraction and machine learning techniques. Four types of kernels namely the Radial Basis Function (RBF), linear, polynomial and sigmoid are applied to test the accuracy of the classification. The results show that the accuracy percentage of web document classification will increase whenever more web document is used. The results also show that linear kernel technique is the best in web document classification compared to RBF, polynomial and sigmoid.

关键词： Testing HTML Europe Astronomy Accuracy Finance Biology

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IMAGE RETRIEVAL USING CONTOUR FEATURE WITH ROUGH SET METHOD

IMAGE RETRIEVAL USING CONTOUR FEATURE WITH ROUGH SET METHOD

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2010 International Conference on computer,Mechatronics,Control and Electronic Engineering(2010计算机、机电、控制与电子工程国际会议 CMCE 2010)

作者： Pheerawit Wasinphongwanit Pisit Phokharatkul Technology of Information System Management Faculty of Engineering Mahidol University Nakhon Pathom Department of Computer Engineering Faculty of Engineering Mahidol University Nakhon Pathom73170 Tha

Content based image retrieval (CBIR) is well-known in the field of image retrieval. It uses contents of an image from image processing and analysis to retrieve images that users were looking for from an image search. Shape based image retrieval was focused in this paper. A data mining was considered to find knowledge in the image database. Fourier descriptor is a most technique to extract contour feature of images. It was used to analyze the testing and training images in the preprocessing step. Fourier coefficients were quantized into multiple attributes and rough set theory was used to generate a rule-based system. Rough set theory is used as a data mining technique. It was compared to similarity measurement We use 15,984 testing image data with 71,928 training image data in this experiment. A total usage time of rough set method is 13,286 seconds. A total usage time of similarity measurement is 19365 seconds. A total usage memory of rough set method and similarity measurement are 2.8 Mbytes and 8. 6 Mbytes respectively. An average precision, an average recall and an average accuracy of rough set method are 0.1297, 0.261 and 0.9971. An average precision, an average recall and an average accuracy of similarity measurement are 0.1619, 0.9651 and 0.9852. The rough set method is advantage to the usage time and the usage memory.

关键词： Rough set Image retrieval Fourier descriptors

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Notice of Retraction: Framework of intelligent game and software for improvement of learning performance based on heart rate variability

Notice of Retraction: Framework of intelligent game and soft...

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International Conference on computer Engineering and technology, ICCET

作者： Noaziah Ahmad A.H. Beg Ahmad N Abdalla Muhammad Nubli Nawsher Khan Ainul Azila Faculty of Computer System and Software Engineering Universiti Malaysia Pahang Malaysia Faculty of Electronics and Electrical Engineering Universiti Malaysia Pahang Malaysia Faculty of Technology Management Universiti Malaysia Pahang Malaysia

This article has been retracted by the publisher.

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First order statistical feature for breast cancer detection using thermal images

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World Academy of Science, Engineering and technology 2010年 46卷 424-426页

作者： Nurhayati, Oky Dwi Widodo, Thomas Sri Susanto, Adhi Tjokronagoro, Maesadji Department of Computer System Faculty of Engineering University of Diponegoro Indonesia Department of Electrical Engineering and Information Technology Faculty of Engineering Gadjah Mada University Yogyakarta Indonesia Department of Medical Faculty of Medicine Gadjah Mada University Yogyakarta India

In this paper, we report our experimentation to reveal the abnormalities of breast thermograms with tabulated the first order statistics method which are the mean values, standard deviation values, skewness values, and kurtosis values with thermal camera Fluke as a tool for capturing images, after the applications of wiener filter and histogram equalization to enhance the images and region of interest to obtain the specific object. We have used statistical features method to classify types of thermograms after image processing. The results show that the method are promising to detect the abnormality on the breast thermogram images. The normal breast thermograms have minimum standard deviation value and skewness value which differ from those abnormal thermograms in the early stage of breast cancer and the significantly from the advanced of breast cancer.

关键词： Image enhancement

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Research on the Self-Shrinking 2-Adic Cryptographic Generator

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通讯和计算机（中英文版） 2010年第11期7卷 67-71页

作者： Borislav Stoyanov Aleksandar Milev Anatoli Nachev Faculty of Computer Informatics University of Shumen ＂＇Bishop Konstantin Preslavski Shumen 9700 Bulgaria Faculty of Computer System and Technology University of Shumen ＂＇Bishop Konstantin Preslavski Shumen 9700 Bulgaria Business Information Systems Cairnes Business School NUI Galway Ireland

The Self-shrinking 2-adic cryptographic generator (SS2CG) is investigated in this paper. The period and the linear complexity of the generated sequenced has been presented. The SS2CG generator is developed by suitable software and the speed of generated pseudorandom sequence is tested through a fast software stream cipher. The cryptography resistance of the output generated pseudorandom sequence is analyzed and statistic researches are evaluated by NIST test suite. The generated sequence has a large period, large linear complexity and is stable against the cryptographic attacks. The SS2CG is suitable for critical cryptographic applications in stream cipher encryption algorithms for increasing security in wireless networks and communication systems.

关键词：加密技术发生器进制自缩伪随机序列线性复杂度测试套件 NIST

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Interpretative Key Management (IKM), A Novel Framework

Interpretative Key Management (IKM), A Novel Framework

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International Conference on computer Research and Development (ICCRD)

作者： Saman Shojae Chaeikar Shukor Abd Razak Shohreh Honarbakhsh Hossein Rouhani Zeidanloo Mazdak Zamani Farhang Jaryani Centre for Advanced Software Engineering University Technology of Malaysia Kuala Lumpur Malaysia Faculty of Computer Science and Information System University Technology of Malaysia Kuala Lumpur Malaysia

ISBN: (纸本)9781424469925;9780769540436

Nowadays, we use cryptography keys to secure our communications. One of the common ways for securing data exchanging is via the use of symmetric keys to encipher transmitted data over network. Today's practices for managing keys face many issues in key generation, distribution, and revocation. In this paper we propose interpretative key management method which is simpler than the current practices. Eliminating the need for key storage, the need for key distribution, automatic key revocation, and unique key per session are the main features of the new proposed key management method. Deletion of some steps and replacing some others with new ones helped us to dominate many issues faced with common practices of key management.

关键词： Public key cryptography Research and development Conference management Research and development management Software development management technology management Engineering management Software engineering computer science Management information systems

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Content-based retrieval by multiple image examples for sign board retrieval

Content-based retrieval by multiple image examples for sign ...

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28th Picture Coding Symposium, PCS 2010

作者： Yoshitaka, Atsuo Hyoudou, Terumasa School of Information Science Japan Advanced Institute of Science and Technology 1-1 Asahidai Nomi Ishikawa 923-1292 Japan Faculty of Engineering Hiroshima University 1-4-1 Kagamiyama Higashi-Hiroshima 739-8527 Japan Computer System Co. Ltd. Japan

ISBN: (纸本)9781424471348

In the area of retrieving image databases, one of the promising approaches is to retrieve it by specifying image example. However, specifying a single image example is not always sufficient to get satisfactory result, since one image example does not give comprehensive ranges of values that reflect the various aspects of the object to be retrieved. In this paper, we propose a method of retrieving images by specifying multiple image examples that is designed for retrieving sign boards. Features of color, shape, and spatial relation of color regions are extracted from example images, and they are clustered so as to obtain proper range of values. Compared with QBE systems that accept only a single image as the query condition, MIERS (Multi-Image Example-based Retrieval system) returns better retrieval result, where the experimental result showed that specifying more examples helps to improve recall with little deterioration of precision. © 2010 IEEE.

关键词： Content based retrieval

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