Identity Security in the AI Era (Gupta Ankit) (z-library.sk, 1lib.sk, z-lib.sk)

【One-Line Pitch】 A practitioner's field guide to defending digital identities when both attackers and defenders wield AI, showing how zero trust, identity-first architecture, and adaptive controls fit together in real enterprises. Best for CISOs, identity engineers, architects, and policy professionals who need a roadmap rather than theory. 【Book Arc】 - **Opening (~0%–10%)**: Frames identity as the new perimeter and explains why firewalls and VPNs no longer define trust boundaries; establishes the vocabulary (IAM, MFA, PAM, IGA, Zero Trust) that the rest of the book assumes. - **Early (~10%–30%)**: Lays the foundation with Zero Trust fundamentals for AI-driven organizations, including NIST 800-207 alignment and hybrid on-prem/cloud identity architectures, then illustrates the stakes through cross-sector breach case studies (finance, healthcare, manufacturing, government). - **Middle (~30%–55%)**: Moves into identity inside AI pipelines — machine and workload identities, identity management across the AI development lifecycle, and securing autonomous agents and AI services — while introducing adaptive access controls, contextual authentication, and behavior-based risk scoring. - **Late (~55%–85%)**: Shifts to detection and response: identity threat detection and response (ITDR), UEBA-driven anomaly detection, and how to detect and contain identity attacks once prevention fails. - **Ending (~85%–100%)**: Zooms out to cross-platform identity security patterns and a forward-looking view of identity security in an AI-driven world, tying the layers together into a single strategic picture. 【Key Takeaways】 - **Identity, not the network, is the security boundary** (Early): Every login, API call, and device connection must be tied to an authenticated identity and governed by policy — "never trust, always verify" replaces "inside vs. outside." - **AI cuts both ways** (Early): Adversaries use AI for convincing phishing and deepfake impersonation, while defenders use AI-driven behavior analytics; the book treats this arms race as the baseline assumption, not an edge case. - **Machine and workload identities are first-class citizens** (Middle): Service accounts, API keys, bots, and autonomous agents all carry identities that need lifecycle management, least privilege, and just-in-time access — a gap many enterprises still under-manage. - **One weak identity can collapse the whole chain** (Early): The case studies repeatedly show a single account without MFA or a reused contractor password leading to catastrophic breaches; MFA and privileged access controls are non-negotiable. - **Adaptive, context-aware controls beat static rules** (Middle): Conditional access, continuous evaluation, and risk scoring let policy respond to changing conditions rather than granting blanket trust at login. - **Detection and response are part of identity security** (Late): ITDR and UEBA matter because attackers increasingly "live off the land" with legitimate credentials, evading perimeter alarms. - **Third parties and OT expand the identity surface** (Middle): Contractors, suppliers, and operational technology systems need unique identities, time-boxed access, and segmentation — IAM must bridge IT and OT. - **The future is layered and post-quantum-aware** (Ending): Cross-platform patterns and readiness for emerging threats (adversarial AI, supply chain, post-quantum) require identity strategy to span multiple layers of the stack. 【Reading Tips】 - **Skim the glossary and acronym list first** (~6%–20%): It is dense but pays off — the book uses IAM, ITDR, UEBA, CAEP, and similar terms constantly. - **Deep-read the case studies** (Early): They are the most concrete material and translate abstract principles into memorable lessons; use them to justify budget and policy changes internally. - **Treat Parts II–III as the working core** (Middle–Late): Machine identities, agent security, and adaptive controls are where most practitioners will find actionable design guidance. - **Don't expect code or deep configuration walkthroughs**: The book is framework- and pattern-oriented; pair it with vendor documentation (e.g., Entra, cloud IAM) for implementation detail. - **Use the end-of-chapter takeaways as a checklist**: The book explicitly builds in summary points — turn them into an assessment rubric for your own environment. 【Coverage Limits】 This guide is based on stratified excerpts covering the front matter, glossary, Part I foundations, and portions of the middle and late chapters; specific chapter-level detail in Parts II–IV (agent security, ITDR mechanics, cross-platform patterns) is only partially represented, so treat the arc as directional rather than exhaustive.