 |
||||
| Gupta, Brij, Sheng, Quan Z | ||||
| CRC Press | ||||
| 2019 | ||||
| English | ||||
| 352 pages | ||||
| 18.79 | ||||
[tab] [content title="Summary"] **Abstract:** While **Computer Security** is a broad field encompassing various technologies, protocols, standards, and policies designed to protect computing systems—including hardware, software, and the information they contain—**Cyber Security** is a more specific and rapidly growing domain focused on safeguarding computer networks (both online and offline) from threats such as unauthorized access, botnets, phishing scams, and more. **Machine Learning**, a subfield of Computer Science, enables machines to learn and adapt based on observable and verifiable data. In the context of cyber security, machine learning can be leveraged to enhance the protection of computer systems and information by detecting anomalies and threats through data mining and other advanced techniques. This book serves as an essential resource for understanding how machine learning and data mining can be applied to improve computer and cyber security. It offers in-depth coverage of critical security issues in the realm of both computer and cyber security, alongside analyses of machine learning and data mining-based solutions. Furthermore, the book explores promising future research areas where these technologies can further contribute to combating cyber threats. The book is particularly valuable for IT professionals, researchers, faculty members, scientists, graduate students, research scholars, and software developers who are interested in researching and developing solutions to address cyber security challenges using machine learning-based approaches. It is an invaluable resource for readers from **Computer Science and Engineering** fields, as well as **Cyber Security** professionals, offering both foundational and cutting-edge insights. ### **Key Features:** - **Illustrative Examples & Case Studies:** The book includes numerous examples and illustrations that demonstrate key principles, algorithms, challenges, and applications of machine learning and data mining in the context of computer and cyber security. - **Security Aspects & Current Trends:** The book covers the most important security issues in the field and highlights the latest trends and developments in cyber defense. - **Future Research Directions:** Insights into emerging research areas where machine learning and data mining solutions can be applied to combat cyber threats more effectively. - **Practical Defense Strategies:** The book helps students and practitioners understand the motivations behind cyber attacks, and how machine learning can be employed to better defend against, detect, and mitigate these threats. This book is an extensive guide to both the theoretical and practical aspects of applying machine learning techniques to computer and cyber security. It prepares readers to confront real-world security challenges using cutting-edge technologies and offers a comprehensive framework for future research and development in the field. [/content] [content title="Content"] [/content] [content title="Author(s)"] [/content] [/tab]
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