 Название: Machine Learning for Cybersecurity: Innovative Deep Learning Solutions
Автор: Marwan Omar
Издательство: Springer
Год: 2022
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB
This SpringerBrief presents the underlying principles of Machine Learning (ML) and how to deploy various Deep Learning (DL) 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.
As cybersecurity threats keep growing exponentially in scale, frequency, and impact, legacy-based threat detection systems have proven inadequate. This has prompted the use of machine learning (hereafter, ML) to help address the problem. But as organizations increasingly use intelligent cybersecurity techniques, the over-all efficacy and benefit analysis of these ML-based digital security systems remain a subject of increasing scholarly inquiry. The present study seeks to expand and add to this growing body of literature by demonstrating the applications of ML-based data analysis techniques to various problem domains in cybersecurity. To achieve this objective, a rapid evidence assessment (REA) of existing scholarly literature on the subject matter is adopted. The aim is to present a snapshot of the various ways ML is being applied to help address cybersecurity threat challenges.
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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Machine Learning for Cybersecurity: Innovative Deep Learning Solutions 
