Machine Learning for Cybersecurity

Innovative Deep Learning Solutions de

Éditeur :

Springer


Paru le : 2022-09-24

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Description


This SpringerBrief presents the underlying principles of machine learning and how to deploy various deep learning tools and techniques to tackle and solve certain challenges facing the cybersecurity industry.


By implementing innovative deep learning solutions, cybersecurity researchers, students and practitioners can analyze patterns and learn how to prevent cyber-attacks and respond to changing malware behavior. 


The knowledge and tools introduced in this brief can also assist cybersecurity teams to become more proactive in preventing threats and responding to active attacks in real time. It can reduce the amount of time spent on routine tasks and enable organizations to use their resources more strategically. In short, the knowledge and techniques provided in this brief can help make cybersecurity simpler, more proactive, less expensive and far more effective


Advanced-level students in computer science studying machine learning with a cybersecurity focus will find this SpringerBrief useful as a study guide. Researchers and cybersecurity professionals focusing on the application of machine learning tools and techniques to the cybersecurity domain will also want to purchase this SpringerBrief.
Pages
48 pages
Collection
n.c
Parution
2022-09-24
Marque
Springer
EAN papier
9783031158926
EAN PDF
9783031158933

Informations sur l'ebook
Nombre pages copiables
0
Nombre pages imprimables
4
Taille du fichier
2560 Ko
Prix
58,01 €
EAN EPUB
9783031158933

Informations sur l'ebook
Nombre pages copiables
0
Nombre pages imprimables
4
Taille du fichier
8151 Ko
Prix
58,01 €

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