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Twitter Spam Detection and Traffic Classification
Publicado por
LAP LAMBERT Academic Publishing Jul 2023, 2023
ISBN 10: 6206737055
ISBN 13: 9786206737056
Nuevo
Taschenbuch
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The rapid growth of the Internet and social media has led to an increase in the size of Internet traffic and the complexity of analyzing traffic behavior, especially in large-scale networks like social media platforms. Traditional rule-based methodologies are being replaced by automated approaches powered by machine learning, driven by the availability of large datasets that enable high-performance AI models. This book reviews recent research on cyber traffic analysis over social networks and the Internet, focusing on similarity, correlation, and collective indication concepts, and emphasizing the importance of security goals in classifying network hosts, applications, users, and tweets. To tackle these challenges, the paper introduces a new research methodology called data-driven cyber security (DDCS) and its application in analyzing social and Internet traffic. The DDCS methodology consists of three main components: cyber security data processing, cyber security feature engineering, and cyber security modeling. 76 pp. Englisch. Nº de ref. del artículo: 9786206737056
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Twitter Spam Detection and Traffic Classification
Publicado por
LAP Lambert Academic Publishing, 2023
ISBN 10: 6206737055
ISBN 13: 9786206737056
Nuevo
Tapa blanda
Librería: moluna, Greven, Alemania
Calificación del vendedor: 5 de 5 estrellas
Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The rapid growth of the Internet and social media has led to an increase in the size of Internet traffic and the complexity of analyzing traffic behavior, especially in large-scale networks like social media platforms. Traditional rule-based methodologies a. Nº de ref. del artículo: 1023592000
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Twitter Spam Detection and Traffic Classification : A data-driven cyber security approach
Publicado por
LAP LAMBERT Academic Publishing, 2023
ISBN 10: 6206737055
ISBN 13: 9786206737056
Nuevo
Taschenbuch
Librería: AHA-BUCH GmbH, Einbeck, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The rapid growth of the Internet and social media has led to an increase in the size of Internet traffic and the complexity of analyzing traffic behavior, especially in large-scale networks like social media platforms. Traditional rule-based methodologies are being replaced by automated approaches powered by machine learning, driven by the availability of large datasets that enable high-performance AI models. This book reviews recent research on cyber traffic analysis over social networks and the Internet, focusing on similarity, correlation, and collective indication concepts, and emphasizing the importance of security goals in classifying network hosts, applications, users, and tweets. To tackle these challenges, the paper introduces a new research methodology called data-driven cyber security (DDCS) and its application in analyzing social and Internet traffic. The DDCS methodology consists of three main components: cyber security data processing, cyber security feature engineering, and cyber security modeling. Nº de ref. del artículo: 9786206737056
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Twitter Spam Detection and Traffic Classification
Publicado por
LAP LAMBERT Academic Publishing Jul 2023, 2023
ISBN 10: 6206737055
ISBN 13: 9786206737056
Nuevo
Taschenbuch
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The rapid growth of the Internet and social media has led to an increase in the size of Internet traffic and the complexity of analyzing traffic behavior, especially in large-scale networks like social media platforms. Traditional rule-based methodologies are being replaced by automated approaches powered by machine learning, driven by the availability of large datasets that enable high-performance AI models. This book reviews recent research on cyber traffic analysis over social networks and the Internet, focusing on similarity, correlation, and collective indication concepts, and emphasizing the importance of security goals in classifying network hosts, applications, users, and tweets. To tackle these challenges, the paper introduces a new research methodology called data-driven cyber security (DDCS) and its application in analyzing social and Internet traffic. The DDCS methodology consists of three main components: cyber security data processing, cyber security feature engineering, and cyber security modeling.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 76 pp. Englisch. Nº de ref. del artículo: 9786206737056
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Twitter Spam Detection and Traffic Classification | A data-driven cyber security approach
Publicado por
LAP LAMBERT Academic Publishing, 2023
ISBN 10: 6206737055
ISBN 13: 9786206737056
Nuevo
Taschenbuch
Librería: preigu, Osnabrück, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: Neu. Twitter Spam Detection and Traffic Classification | A data-driven cyber security approach | Soumitra Das (u. a.) | Taschenbuch | Englisch | 2023 | LAP LAMBERT Academic Publishing | EAN 9786206737056 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Nº de ref. del artículo: 127346601
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