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.
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