Details
Autonomous Data Security
Creating a Proactive Enterprise Protection Plan|
59,99 € |
|
| Verlag: | Apress |
| Format: | |
| Veröffentl.: | 07.10.2024 |
| ISBN/EAN: | 9798868808388 |
| Sprache: | englisch |
| Anzahl Seiten: | 200 |
Dieses eBook enthält ein Wasserzeichen.
Beschreibungen
<p>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.</p>
<p>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.</p>
<p>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.</p>
<p><strong>What You Will learn:</strong></p>
<ul>
<li>Understand why data security is important for enterprise businesses.</li>
<li>How data protection solutions work and how to evaluate a solution in the market.</li>
<li>How to start thinking and evaluating requirements when building a solution for small, medium, and large enterprises.</li>
<li>Understand the pros and cons of security policy configurations defined by administrators and why can’t they provide comprehensive protection.</li>
<li>How to safeguard data via adaptive learning from the deployed environment – providing autonomous data security with or without policies.</li>
<li>How to leverage AI to provide data security with comprehensive proactive protection.</li>
<li>What factors to consider when they have to protect and safeguard data.</li>
</ul>
<p><strong>Who this book is for:</strong></p>
<p>The primary audience is cybersecurity professionals, security enthusiasts, C-level executives in organizations (all verticals), and security analysts and IT administrators. Secondary audience includes professors and teachers, channel integrators, professional services, and hackers.</p>
<p>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.</p>
<p>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.</p>
<p><strong>What You Will learn:</strong></p>
<ul>
<li>Understand why data security is important for enterprise businesses.</li>
<li>How data protection solutions work and how to evaluate a solution in the market.</li>
<li>How to start thinking and evaluating requirements when building a solution for small, medium, and large enterprises.</li>
<li>Understand the pros and cons of security policy configurations defined by administrators and why can’t they provide comprehensive protection.</li>
<li>How to safeguard data via adaptive learning from the deployed environment – providing autonomous data security with or without policies.</li>
<li>How to leverage AI to provide data security with comprehensive proactive protection.</li>
<li>What factors to consider when they have to protect and safeguard data.</li>
</ul>
<p><strong>Who this book is for:</strong></p>
<p>The primary audience is cybersecurity professionals, security enthusiasts, C-level executives in organizations (all verticals), and security analysts and IT administrators. Secondary audience includes professors and teachers, channel integrators, professional services, and hackers.</p>
<p>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.</p>
<p><strong>Priyanka Neelakrishnan</strong> is a distinguished data security expert with over a decade of experience in building world-class data protection solutions. Her illustrious career includes pivotal roles at renowned cybersecurity firms such as Palo Alto Networks and Symantec, where she has consistently driven innovation and excellence.</p>
<p>As the Product Line Manager at Palo Alto Networks, Priyanka has been instrumental in conceptualizing, designing, and launching transformative cybersecurity products. Her efforts have led to the widespread adoption of advanced information protection solutions, significantly enhancing enterprise security. During her tenure at Symantec (now Broadcom), Priyanka spearheaded initiatives in on-prem, cloud, and hybrid data protection, notably developing the industry's first cloud data protection solution tailored for large enterprise customers. This groundbreaking solution encompassed all major cloud channels, including Email, Web, and Applications, and featured patented content detection technologies.</p>
<p> </p>
<p>Recognized as a go-to authority in the field of data protection, Priyanka is highly regarded for her mentoring capabilities and expertise across a wide range of data security topics. She is also a renowned speaker and independent researcher, contributing extensively to the advancement of the cybersecurity field. Her innovative products and strategic insights have earned her leadership and excellence awards, underscoring her significant contributions to the cybersecurity landscape.</p>
<p>As the Product Line Manager at Palo Alto Networks, Priyanka has been instrumental in conceptualizing, designing, and launching transformative cybersecurity products. Her efforts have led to the widespread adoption of advanced information protection solutions, significantly enhancing enterprise security. During her tenure at Symantec (now Broadcom), Priyanka spearheaded initiatives in on-prem, cloud, and hybrid data protection, notably developing the industry's first cloud data protection solution tailored for large enterprise customers. This groundbreaking solution encompassed all major cloud channels, including Email, Web, and Applications, and featured patented content detection technologies.</p>
<p> </p>
<p>Recognized as a go-to authority in the field of data protection, Priyanka is highly regarded for her mentoring capabilities and expertise across a wide range of data security topics. She is also a renowned speaker and independent researcher, contributing extensively to the advancement of the cybersecurity field. Her innovative products and strategic insights have earned her leadership and excellence awards, underscoring her significant contributions to the cybersecurity landscape.</p>
<p>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.</p>
<p>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.</p>
<p>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.</p>
<p><strong>What You Will Learn:</strong></p>
<ul>
<li>Understand why data security is important for enterprise businesses.</li>
<li>Learn how data protection solutions work and how to evaluate solutions in the market.</li>
<li>Discover how to start thinking and evaluating requirements when building solutions for small, medium, and large enterprises given data protection is your utmost priority.</li>
<li>Understand the pros and cons of security policy configurations defined by administrators and why they can’t provide comprehensive protection.</li>
<li>Learn how to safeguard data via adaptive learning from the deployed environment – providing autonomous data security with minimal policies.</li>
<li>Discover how to build self-learning adaptable intelligent systems to provide data security with comprehensive proactive protection.</li>
</ul>
<p>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.</p>
<p>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.</p>
<p><strong>What You Will Learn:</strong></p>
<ul>
<li>Understand why data security is important for enterprise businesses.</li>
<li>Learn how data protection solutions work and how to evaluate solutions in the market.</li>
<li>Discover how to start thinking and evaluating requirements when building solutions for small, medium, and large enterprises given data protection is your utmost priority.</li>
<li>Understand the pros and cons of security policy configurations defined by administrators and why they can’t provide comprehensive protection.</li>
<li>Learn how to safeguard data via adaptive learning from the deployed environment – providing autonomous data security with minimal policies.</li>
<li>Discover how to build self-learning adaptable intelligent systems to provide data security with comprehensive proactive protection.</li>
</ul>
Gain insights into the pros and cons of various data protection measures Safeguard data, address insider threats, and maximize security policies and AI-driven solutions Review actionable recommendations and best practices for safeguarding data
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