You might also like

More about Machine Learning for Cybersecurity

• Book details
• Synopsis
• Trending among others

You get 154 loyalty points

Book synopsis

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 effectiveAdvanced-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.

Book details

Book category Books in English Computing & information technology Computer science Artificial intelligence

• Full title: Machine Learning for Cybersecurity
• Subtitle: Innovative Deep Learning Solutions
• Author: Marwan Omar
• Language: English
• Binding: Paperback
• Number of pages: 48
• EAN: 9783031158926
• ID: 39511298
• Publisher: Springer, Berlin
• Weight: 102 g
• Dimensions: 235 × 155 × 4 mm
• Published: 2022

Trending among others

---

---

---