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Multiple-Feature Extracting Modules Based Leak Mining System Design
Joint Authors
Source
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-12-17
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
Over the years, human dependence on the Internet has increased dramatically.
A large amount of information is placed on the Internet and retrieved from it daily, which makes web security in terms of online information a major concern.
In recent years, the most problematic issues in web security have been e-mail address leakage and SQL injection attacks.
There are many possible causes of information leakage, such as inadequate precautions during the programming process, which lead to the leakage of e-mail addresses entered online or insufficient protection of database information, a loophole that enables malicious users to steal online content.
In this paper, we implement a crawler mining system that is equipped with SQL injection vulnerability detection, by means of an algorithm developed for the web crawler.
In addition, we analyze portal sites of the governments of various countries or regions in order to investigate the information leaking status of each site.
Subsequently, we analyze the database structure and content of each site, using the data collected.
Thus, we make use of practical verification in order to focus on information security and privacy through black-box testing.
American Psychological Association (APA)
Cho, Ying-Chiang& Pan, Jen-Yi. 2013. Multiple-Feature Extracting Modules Based Leak Mining System Design. The Scientific World Journal،Vol. 2013, no. 2013, pp.1-11.
https://search.emarefa.net/detail/BIM-1012756
Modern Language Association (MLA)
Cho, Ying-Chiang& Pan, Jen-Yi. Multiple-Feature Extracting Modules Based Leak Mining System Design. The Scientific World Journal No. 2013 (2013), pp.1-11.
https://search.emarefa.net/detail/BIM-1012756
American Medical Association (AMA)
Cho, Ying-Chiang& Pan, Jen-Yi. Multiple-Feature Extracting Modules Based Leak Mining System Design. The Scientific World Journal. 2013. Vol. 2013, no. 2013, pp.1-11.
https://search.emarefa.net/detail/BIM-1012756
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1012756