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Cloud Computing Anomaly and Threat Detection: Using Big Data Analytics and Machine Learning - Softcover
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While leveraging cloud computing for large-scale distributed applications allows seamless scaling, many companies struggle following up with the amount of data generated in terms of efficient processing and anomaly detection. With the rapid growth of web attacks, anomaly detection becomes a necessary part of the management of modern large-scale distributed web applications. As the record of user behavior, weblogs certainly become the research object related to anomaly detection. Many anomaly detection methods based on automated log analysis have been proposed. However, not in the context of big data applications where normal and anomalous behavior models need to be constructed before prediction attempts.To address this problem, Big Data Analytics and Machine Learning algorithms in overcoming the challenges of data processing, pattern detection, and anomaly prediction in large and high-dimensional data representing user and application logs are utilized.
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Cloud Computing Anomaly and Threat Detection: Using Big Data Analytics and Machine Learning
Published by
LAP LAMBERT Academic Publishing, 2021
ISBN 10: 6204719041
ISBN 13: 9786204719047
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Softcover
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Cloud Computing Anomaly and Threat Detection
Published by
LAP LAMBERT Academic Publishing Nov 2021, 2021
ISBN 10: 6204719041
ISBN 13: 9786204719047
New
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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -While leveraging cloud computing for large-scale distributed applications allows seamless scaling, many companies struggle following up with the amount of data generated in terms of efficient processing and anomaly detection. With the rapid growth of web attacks, anomaly detection becomes a necessary part of the management of modern large-scale distributed web applications. As the record of user behavior, weblogs certainly become the research object related to anomaly detection. Many anomaly detection methods based on automated log analysis have been proposed. However, not in the context of big data applications where normal and anomalous behavior models need to be constructed before prediction attempts.To address this problem, Big Data Analytics and Machine Learning algorithms in overcoming the challenges of data processing, pattern detection, and anomaly prediction in large and high-dimensional data representing user and application logs are utilized. 112 pp. Englisch. Seller Inventory # 9786204719047
Quantity: 2 available
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Cloud Computing Anomaly and Threat Detection: Using Big Data Analytics and Machine Learning
Published by
LAP LAMBERT Academic Publishing, 2021
ISBN 10: 6204719041
ISBN 13: 9786204719047
New
Softcover
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Seller rating 5 out of 5 stars
Condition: New. Print on Demand. Seller Inventory # 401391469
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Cloud Computing Anomaly and Threat Detection: Using Big Data Analytics and Machine Learning
Published by
LAP LAMBERT Academic Publishing, 2021
ISBN 10: 6204719041
ISBN 13: 9786204719047
New
Softcover
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Cloud Computing Anomaly and Threat Detection
Published by
LAP LAMBERT Academic Publishing, 2021
ISBN 10: 6204719041
ISBN 13: 9786204719047
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Softcover
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Muzaferija IbrahimIbrahim Muzaferija is a researcher, experienced software engineer and machine learning specialist, currently working as a data scientist. He creates links between academia and industry, solves cross-industry problem. Seller Inventory # 537543957
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Cloud Computing Anomaly and Threat Detection
Published by
LAP LAMBERT Academic Publishing Nov 2021, 2021
ISBN 10: 6204719041
ISBN 13: 9786204719047
New
Taschenbuch
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Taschenbuch. Condition: Neu. Neuware -While leveraging cloud computing for large-scale distributed applications allows seamless scaling, many companies struggle following up with the amount of data generated in terms of efficient processing and anomaly detection. With the rapid growth of web attacks, anomaly detection becomes a necessary part of the management of modern large-scale distributed web applications. As the record of user behavior, weblogs certainly become the research object related to anomaly detection. Many anomaly detection methods based on automated log analysis have been proposed. However, not in the context of big data applications where normal and anomalous behavior models need to be constructed before prediction attempts.To address this problem, Big Data Analytics and Machine Learning algorithms in overcoming the challenges of data processing, pattern detection, and anomaly prediction in large and high-dimensional data representing user and application logs are utilized.Books on Demand GmbH, Überseering 33, 22297 Hamburg 112 pp. Englisch. Seller Inventory # 9786204719047
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Cloud Computing Anomaly and Threat Detection : Using Big Data Analytics and Machine Learning
Published by
LAP LAMBERT Academic Publishing, 2021
ISBN 10: 6204719041
ISBN 13: 9786204719047
New
Taschenbuch
Seller: AHA-BUCH GmbH, Einbeck, Germany
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - While leveraging cloud computing for large-scale distributed applications allows seamless scaling, many companies struggle following up with the amount of data generated in terms of efficient processing and anomaly detection. With the rapid growth of web attacks, anomaly detection becomes a necessary part of the management of modern large-scale distributed web applications. As the record of user behavior, weblogs certainly become the research object related to anomaly detection. Many anomaly detection methods based on automated log analysis have been proposed. However, not in the context of big data applications where normal and anomalous behavior models need to be constructed before prediction attempts.To address this problem, Big Data Analytics and Machine Learning algorithms in overcoming the challenges of data processing, pattern detection, and anomaly prediction in large and high-dimensional data representing user and application logs are utilized. Seller Inventory # 9786204719047
Quantity: 1 available