Machine learning approaches in cyber security analytics / / Tony Thomas, Athira P. Vijayaraghavan, Sabu Emmanuel

• Record Nr.: UNINA9910366657003321
• Autore: Thomas Tony
• Pubbl/distr/stampa: Singapore : , : Springer Singapore : , : Imprint : Springer, , [2020]
• ISBN: 9789811517068; 981-15-1706-1
• Descrizione fisica: 1 online resource (217 pages)
• Disciplina: 005.8
• Soggetti: Computer security; Application software; Data encryption (Computer science); Computer crimes; Data structures (Computer science); Seguretat informàtica; Xifratge (Informàtica); Aprenentatge automàtic; Delictes informàtics; Systems and Data Security; Information Systems Applications (incl. Internet); Cryptology; Cybercrime; Data Structures
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di contenuto: 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.
• Sommario/riassunto: 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 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. .