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Design Pattern Mining Using graph Matching

Wuhan University Journal of Natural Sciences 2004年第4期9卷 444-448页

作者： LIQing-hua ZHANGZhi-xiang BENKe-rong SchoolofComputerScienceandTechnology HuazhongUniversityofScienceandTechnologyWuhan430074HubeiChina DepartmentofComputerScience NavalUniversityofEngineeringWuhan430033HubeiChina

The identification of design pattern instances is important for program understanding and software maintenance. Aiming at the mining of design patterns in existing systems, this paper proposes a subgraph isomorphism approach to discover several design patterns in a legacy system at a time. The attributed relational graph is used to describe design patterns and legacy systems. The sub-graph isomorphism approach consists of decomposition and composition process. During the decomposition process, graphs corresponding to the design patterns are decomposed into sub-graphs, some of which are graphs corresponding to the elemental design patterns. The composition process tries to get sub-graph isomorphism of the matched graph if sub-graph isomorphism of each subgraph is obtained. Due to the common structures between design patterns, the proposed approach can reduce the matching times of entities and relations. Compared with the existing methods, the proposed algorithm is not linearly dependent on the number of design pattern graphs. Key words design pattern mining - attributed relational graph - subgraph isomorphism CLC number TP 311.5 Foundation item: Supported by the National Natural Science Foundation of China (60273075) and the Science Foundation of Naval University of Engineering (HGDJJ03019)Biography: LI Qing-hua (1940-), male, Professor, research direction: parallel computing.

关键词： design pattern mining attributed relational graph subgraph isomorphism

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Architecture and algorithm for web phishing detection

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Journal of Southeast University(English Edition) 2010年第1期26卷 43-47页

作者：曹玖新王田峰时莉莉毛波东南大学计算机科学与工程学院南京210096 瑞典皇家理工大学结构与建筑环境学院斯德哥尔摩se10044

A phishing detection system, which comprises client-side filtering plug-in, analysis center and protected sites, is proposed. An image-based similarity detection algorithm is conceived to calculate the similarity of two web pages. The web pages are first converted into images, and then divided into sub-images with iterated dividing and shrinking. After that, the attributes of sub-images including color histograms, gray histograms and size parameters are computed to construct the attributed relational graph（ARG）of each page. In order to match two ARGs, the inner earth mover＇s distances（EMD）between every two nodes coming from each ARG respectively are first computed, and then the similarity of web pages by the outer EMD between two ARGs is worked out to detect phishing web pages. The experimental results show that the proposed architecture and algorithm has good robustness along with scalability, and can effectively detect phishing.

关键词： phishing detection image similarity attributed relational graph inner EMD outer EMD

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