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Security

As explained in Data-Driven Cybersecurity

Information security is the protection of information and information systems from unauthorized access, use, disclosure, disruption, modification, or destruction.

Security protects information and the systems that hold it throughout the data life cycle. For critical data, the aims are confidentiality, integrity, and availability. Protection is ongoing: controls need maintenance as threats change. section 7.3 section 7.0

A practical security program combines several kinds of protection:

  • Set access rules and manage identities and credentials so that access to organizational data is controlled. section 7.0 section 7.9
  • Train employees to recognize suspicious activity, and document responsibilities in policies and procedures. section 7.0 section 5.5
  • Plan to detect, respond to, and recover from incidents; one failed control should not become a catastrophic event. section 1.4 section 5.5

A convincing credential request

An employee receives a password-reset email, then a call that sounds like trusted IT staff. The caller directs the employee to a cloned system that captures credentials. The risk is not confined to the email: training and multifactor verification matter when attackers combine channels and voice cloning. section 1.4

Measure whether protection works, not merely whether controls exist. Authentication results and training effectiveness inform access and awareness decisions; encryption use and incident-response success inform data-security decisions. For cloud and hybrid environments, threat-detection and attack-surface metrics add context. AI-assisted detection can help identify changing patterns, but its performance must be evaluated before relying on it. section 7.9 section 10.5 section 12.0

How Data-Driven Cybersecurity covers it

How deep it goes
Defines data-security goals and identifies protective layers, policies, and metrics, without specifying a complete control implementation.
Examples
Illustrates layered protection with a data-vault analogy and multichannel phishing with a voice-cloned IT call.
What it assumes
Introduces data protection through a plain-language analogy; requires Python tools and libraries for the separate machine-learning exercises.
What you can do after
Evaluate/understand security controls using access, training, encryption, incident-response, and availability metrics.
How it connects
Links security to access control, awareness training, incident response, resilience, cloud threat management, and machine learning.

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This explainer was generated by Manning's knowledge graph from the text of Data-Driven Cybersecurity. The section links point to the parts of the book it draws on.