Cloud Computing Anomaly and Threat Detection: Using Big Data Analytics and Machine Learning

Muzaferija, Ibrahim

ISBN 10: 6204719041 / ISBN 13: 9786204719047

Published by LAP LAMBERT Academic Publishing, 2021

About this Item

Seller Inventory # 26396034226

Bibliographic Details

• Title: Cloud Computing Anomaly and Threat Detection: Using Big Data Analytics and Machine Learning
• Publisher: LAP LAMBERT Academic Publishing
• Publication Date: 2021
• Language: English
• ISBN 10: 6204719041
• ISBN 13: 9786204719047
• Binding: Soft cover
• Condition: New

About this title

Synopsis

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.