9786137339336 - analysis of malicious detection of short urls from tweets di pattewar, tareek (9 risultati)
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Da: Books Puddle, New York, NY, U.S.A.Books Puddle
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Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
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Paperback. Condizione: Brand New. 80 pages. 8.66x5.98x0.39 inches. In Stock.
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Da: preigu, Osnabrück, Germaniapreigu
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Taschenbuch. Condizione: Neu. Analysis of Malicious Detection of Short URLs from Tweets | Tareek Pattewar | Taschenbuch | 80 S. | Englisch | 2019 | LAP LAMBERT Academic Publishing | EAN 9786137339336 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbie…ter: preigu.
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Online Social Networks (OSNs) have become fundamental parts of our online lives, and their popularity is increasing at a surprising rate every day. Growing popularity of Twitter has attracted the attention of attackers who attempt…to manipulate the features provided by Twitter to gain some advantage, such as driving Twitter users to other websites that they post as short URLs (Uniform Resource Locators) in their tweets.Even short URLs are also used to avoid sharing overly long URLs and save limited text space in tweets. Significant numbers of URLs shared in the OSNs are shortened URLs. Despite of its potential benefits from genuine usage, attackers use shortened URLs to hide the malicious URLs, which direct users to malicious pages. Although, OSN service providers and URL shortening services utilize certain detection mechanisms to prevent malicious URLs from being shortened, research has found that they fail to do so effectively.In this project, we developed mechanism to develop a machine learning classifier which detect malicious short URLs. And also shows comparative analysis of detection with various methods. 80 pp. Englisch.
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Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
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Condizione: New. Print on Demand.
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Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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Da: moluna, Greven, Germaniamoluna
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Pattewar TareekTareek Pattewar is Assistant Professor, Department of Information Technology, R C Patel Institute of Technology at Shirpur, NMU University. His research focuses on Embedded System, Compu…ter Architecture, Data Mining, a.
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Online Social Networks (OSNs) have become fundamental parts of our online lives, and their popularity is increasing at a surprising rate every day. Growing popularity of Twitter has attracted the attention of attackers who attempt to m…anipulate the features provided by Twitter to gain some advantage, such as driving Twitter users to other websites that they post as short URLs (Uniform Resource Locators) in their tweets.Even short URLs are also used to avoid sharing overly long URLs and save limited text space in tweets. Significant numbers of URLs shared in the OSNs are shortened URLs. Despite of its potential benefits from genuine usage, attackers use shortened URLs to hide the malicious URLs, which direct users to malicious pages. Although, OSN service providers and URL shortening services utilize certain detection mechanisms to prevent malicious URLs from being shortened, research has found that they fail to do so effectively.In this project, we developed mechanism to develop a machine learning classifier which detect malicious short URLs. And also shows comparative analysis of detection with various methods.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 80 pp. Englisch.
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Online Social Networks (OSNs) have become fundamental parts of our online lives, and their popularity is increasing at a surprising rate every day. Growing popularity of Twitter has attracted the attention of attackers who attempt to ma…nipulate the features provided by Twitter to gain some advantage, such as driving Twitter users to other websites that they post as short URLs (Uniform Resource Locators) in their tweets.Even short URLs are also used to avoid sharing overly long URLs and save limited text space in tweets. Significant numbers of URLs shared in the OSNs are shortened URLs. Despite of its potential benefits from genuine usage, attackers use shortened URLs to hide the malicious URLs, which direct users to malicious pages. Although, OSN service providers and URL shortening services utilize certain detection mechanisms to prevent malicious URLs from being shortened, research has found that they fail to do so effectively.In this project, we developed mechanism to develop a machine learning classifier which detect malicious short URLs. And also shows comparative analysis of detection with various methods.
