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1. |
Record Nr. |
UNISA996465446203316 |
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Autore |
Thomas Tony |
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Titolo |
Machine Learning Approaches in Cyber Security Analytics [[electronic resource] /] / by Tony Thomas, Athira P. Vijayaraghavan, Sabu Emmanuel |
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Pubbl/distr/stampa |
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Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020 |
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ISBN |
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Edizione |
[1st ed. 2020.] |
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Descrizione fisica |
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1 online resource (217 pages) |
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Disciplina |
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Soggetti |
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Computer security |
Application software |
Data encryption (Computer science) |
Computer crimes |
Data structures (Computer science) |
Systems and Data Security |
Information Systems Applications (incl. Internet) |
Cryptology |
Cybercrime |
Data Structures |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Chapter 1. Introduction -- Chapter 2. Machine Learning Algorithms -- Chapter 3. Machine Learning in Cyber Security Analytics -- Chapter 4. Applications of Support Vector Machines -- Chapter 5. Applications of Nearest Neighbor -- Chapter 6. Applications of Clustering -- Chapter 7. Applications of Dimensionality Reduction -- Chapter 8. Applications of other Machine Learning Methods. |
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Sommario/riassunto |
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This book introduces various machine learning methods for cyber security analytics. With an overwhelming amount of data being generated and transferred over various networks, monitoring everything that is exchanged and identifying potential cyber threats and attacks poses a serious challenge for cyber experts. Further, as cyber attacks become more frequent and sophisticated, there is a |
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requirement for machines to predict, detect, and identify them more rapidly. Machine learning offers various tools and techniques to automate and quickly predict, detect, and identify cyber attacks. . |
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