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Autonomous data security = creating ...

Neelakrishnan, Priyanka.

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Autonomous data security = creating a proactive enterprise protection plan /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Autonomous data security/ by Priyanka Neelakrishnan.
其他題名:	creating a proactive enterprise protection plan /
作者:	Neelakrishnan, Priyanka.
出版者:	Berkeley, CA :Apress : : 2024.,
面頁冊數:	xix, 365 p. :ill., digital ;24 cm.
內容註:	Chapter 1: Introduction, Data Security, and Fundamental Requirements -- Chapter 2: Tradition Data Security -- Chapter 3: Thinking Outside Norms -- Chapter 4: Policy-Less Data Security -- Chapter 5: AI Driven Data Security -- Chapter 6: Conclusion and Design For the Future -- Chapter 7: Future Ready Data Security.
Contained By:	Springer Nature eBook
標題:	Computer security. -
電子資源:	https://doi.org/10.1007/979-8-8688-0838-8
ISBN:	9798868808388

Autonomous data security = creating a proactive enterprise protection plan /
Neelakrishnan, Priyanka.

Autonomous data securitycreating a proactive enterprise protection plan /[electronic resource] :by Priyanka Neelakrishnan. - Berkeley, CA :Apress :2024. - xix, 365 p. :ill., digital ;24 cm.

Chapter 1: Introduction, Data Security, and Fundamental Requirements -- Chapter 2: Tradition Data Security -- Chapter 3: Thinking Outside Norms -- Chapter 4: Policy-Less Data Security -- Chapter 5: AI Driven Data Security -- Chapter 6: Conclusion and Design For the Future -- Chapter 7: Future Ready Data Security.

This book focuses on analyzing the foundational requirements necessary to construct an autonomous data protection solution for enterprise businesses. It navigates readers through various options and tools, outlining the advantages and disadvantages of each. Covering diverse deployment environments including cloud, on-premises, and hybrid setups, as well as different deployment scales and comprehensive channel coverages, it encourages readers to break away from conventional norms in their approach. By exploring the factors that should be taken into account, the book highlights the significant gap in existing data safeguarding solutions, which often rely solely on configured security policies. It proposes a forward-thinking security approach designed to endure over time, surpassing traditional policies and urging readers to consider proactive autonomous data security solutions. Additionally, it delves into the system's ability to adapt to deployed environments, learn from feedback, and autonomously safeguard data while adhering to security policies. More than just a set of guidelines, this book serves as a catalyst for the future of the cybersecurity industry. Its focus on autonomous data security and its relevance in the era of advancing AI make it particularly timely and essential. What You Will Learn: Understand why data security is important for enterprise businesses. Learn how data protection solutions work and how to evaluate solutions in the market. Discover how to start thinking and evaluating requirements when building solutions for small, medium, and large enterprises given data protection is your utmost priority. Understand the pros and cons of security policy configurations defined by administrators and why they can't provide comprehensive protection. Learn how to safeguard data via adaptive learning from the deployed environment - providing autonomous data security with minimal policies. Discover how to build self-learning adaptable intelligent systems to provide data security with comprehensive proactive protection.

ISBN: 9798868808388

Standard No.: 10.1007/979-8-8688-0838-8doiSubjects--Topical Terms:

540555
Computer security.

LC Class. No.: QA76.9.A25 / N44 2024

Dewey Class. No.: 005.8

Autonomous data security = creating a proactive enterprise protection plan /
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520 $a This book focuses on analyzing the foundational requirements necessary to construct an autonomous data protection solution for enterprise businesses. It navigates readers through various options and tools, outlining the advantages and disadvantages of each. Covering diverse deployment environments including cloud, on-premises, and hybrid setups, as well as different deployment scales and comprehensive channel coverages, it encourages readers to break away from conventional norms in their approach. By exploring the factors that should be taken into account, the book highlights the significant gap in existing data safeguarding solutions, which often rely solely on configured security policies. It proposes a forward-thinking security approach designed to endure over time, surpassing traditional policies and urging readers to consider proactive autonomous data security solutions. Additionally, it delves into the system's ability to adapt to deployed environments, learn from feedback, and autonomously safeguard data while adhering to security policies. More than just a set of guidelines, this book serves as a catalyst for the future of the cybersecurity industry. Its focus on autonomous data security and its relevance in the era of advancing AI make it particularly timely and essential. What You Will Learn: Understand why data security is important for enterprise businesses. Learn how data protection solutions work and how to evaluate solutions in the market. Discover how to start thinking and evaluating requirements when building solutions for small, medium, and large enterprises given data protection is your utmost priority. Understand the pros and cons of security policy configurations defined by administrators and why they can't provide comprehensive protection. Learn how to safeguard data via adaptive learning from the deployed environment - providing autonomous data security with minimal policies. Discover how to build self-learning adaptable intelligent systems to provide data security with comprehensive proactive protection.
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