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Developing cybersecurity programs and policies in an AI-driven world / Omar Santos.
- Format:
- Book
- Author/Creator:
- Santos, Omar, author.
- Series:
- Pearson IT cybersecurity curriculum.
- Pearson IT cybersecurity curriculum
- Language:
- English
- Subjects (All):
- Computer security.
- Artificial intelligence.
- Computer networks--Security measures.
- Computer networks.
- Information technology--Security measures.
- Information technology.
- Physical Description:
- 1 online resource (768 pages) : illustrations
- Edition:
- Fourth edition.
- Place of Publication:
- Hoboken, New Jersey : Pearson, 2024.
- Summary:
- Today, cyberattacks can place entire organizations at risk. Cybersecurity can no longer be delegated to specialists: Success requires everyone to work together, from leaders on down. Developing Cybersecurity Programs and Policies in an AI-Driven World offers start-to-finish guidance for establishing effective cybersecurity in any organization. Drawing on more than two decades of real-world experience, Omar Santos presents realistic best practices for defining policy and governance, ensuring compliance, and collaborating to harden the entire organization. Santos begins by outlining the process of formulating actionable cybersecurity policies and creating a governance framework to support these policies. He then delves into various aspects of risk management, including strategies for asset management and data loss prevention, illustrating how to integrate various organizational functionsfrom HR to physical securityto enhance overall protection. This book covers many case studies and best practices for safeguarding communications, operations, and access; alongside strategies for the responsible acquisition, development, and maintenance of technology. It also discusses effective responses to security incidents. Santos provides a detailed examination of compliance requirements in different sectors and the NIST Cybersecurity Framework.
- Notes:
- OCLC-licensed vendor bibliographic record.
- ISBN:
- 9780138073992
- OCLC:
- 1446223100
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