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Data mining and machine learning in cybersecurity / Sumeet Dua, Xian Du.

By: Dua, Sumeet.
Contributor(s): Du, Xian.
Publisher: Boca Raton : CRC Press, c2011Description: xxii, 234 pages : illustrations ; 25 cm.ISBN: 9781439839423 (hardback : alk. paper); 1439839425 (hardback : alk. paper).Subject(s): Data mining | Machine learning | Computer security | COMPUTERS / Database Management / Data Mining | COMPUTERS / Software Development & Engineering / Systems Analysis & Design | COMPUTERS / Security / GeneralDDC classification: 005.8 Summary: "Introducing basic concepts of machine learning and data mining methodologies for cyber security, this book provides a unified reference for specific machine learning solutions and cybersecurity problems. The authors focus on how to apply machine learning methodologies in cybersecurity, categorizing methods for detecting, scanning, profiling, intrusions, and anomalies. The text presents challenges and solutions in machine learning along with cybersecurity fundamentals. It also describes advanced problems in cybersecurity in the machine learning domain and examines privacy-preserving data mining methods as a proactive security solution"--Summary: "This interdisciplinary assessment is especially useful for students, who typically learn cybersecurity, machine learning, and data mining in independent courses. Machine learning and data mining play significant roles in cybersecurity, especially as more challenges appear with the rapid development of information discovery techniques, such as those originating from the sheer dimensionality and heterogeneous nature of the network data, the dynamic change of threats, and the severe imbalanced classes of normal and anomalous behaviors"--
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005.8 DUA (Browse shelf) 1 Checked out 24/12/2018

Includes bibliographical references and index.

"Introducing basic concepts of machine learning and data mining methodologies for cyber security, this book provides a unified reference for specific machine learning solutions and cybersecurity problems. The authors focus on how to apply machine learning methodologies in cybersecurity, categorizing methods for detecting, scanning, profiling, intrusions, and anomalies. The text presents challenges and solutions in machine learning along with cybersecurity fundamentals. It also describes advanced problems in cybersecurity in the machine learning domain and examines privacy-preserving data mining methods as a proactive security solution"--

"This interdisciplinary assessment is especially useful for students, who typically learn cybersecurity, machine learning, and data mining in independent courses. Machine learning and data mining play significant roles in cybersecurity, especially as more challenges appear with the rapid development of information discovery techniques, such as those originating from the sheer dimensionality and heterogeneous nature of the network data, the dynamic change of threats, and the severe imbalanced classes of normal and anomalous behaviors"--

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