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

By:

Dua, Sumeet

Contributor(s):

Du, Xian

Publication details: Boca Raton : CRC Press, c2011.Description: xxii, 234 pages : illustrations ; 25 cmISBN:

9781439839423 (hardback : alk. paper)
1439839425 (hardback : alk. paper)

Subject(s):

DDC classification:

005.8 22

LOC classification:

QA76.9.D343 D825 2011

Other classification:

COM021030 | COM051240 | COM053000

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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Average rating: 2.0 (1 votes)

Holdings
Item type	Current library	Home library	Call number	Copy number	Status	Date due	Barcode	Item holds
Book	Ayesha Abed Library General Stacks	Ayesha Abed Library General Stacks	005.8 DUA (Browse shelf(Opens below))	1	Checked out	07/07/2024	3010033689

Total holds: 0

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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"--

CSE

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