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Elsevier

Ensuring AI-enabled Zero Trust Security for Smart City and Healthcare Applications Part A

  • 1st Edition, Volume 146 - April 1, 2027
  • Latest edition
  • Editors: S. Krishnaveni, Pethuru Raj, ANNIE UTHRA, Mithileysh Sathiyanarayanan, Robin Ram Mohan Doss
  • Language: English

Ensuring AI-enabled Zero Trust Security for Smart City and Healthcare Applications Part A, published as Volume 146 of the serial Advances in Computers, provides a comprehensive… Read more

Description

Ensuring AI-enabled Zero Trust Security for Smart City and Healthcare Applications Part A, published as Volume 146 of the serial Advances in Computers, provides a comprehensive examination of the convergence of artificial intelligence, Zero Trust security frameworks, smart city infrastructures, and healthcare technologies. The volume explores how AI-driven security architectures can safeguard increasingly interconnected urban and healthcare ecosystems, addressing challenges associated with IoT networks, autonomous vehicles, wearable devices, telemedicine platforms, medical imaging systems, and healthcare data interoperability. It highlights emerging approaches that integrate AI, blockchain, edge computing, digital twins, federated learning, threat intelligence, and quantum computing to strengthen cyber resilience, privacy protection, and trust management across critical applications. By combining foundational concepts with practical implementations and future-oriented perspectives, this volume serves as an authoritative resource for researchers, cybersecurity professionals, healthcare technologists, and smart city stakeholders seeking to develop secure, adaptive, and resilient digital environments.

Key features

  • Examines the foundations and evolution of AI-driven Zero Trust security frameworks for smart cities and healthcare systems
  • Explores AI-enabled protection mechanisms for IoT ecosystems, autonomous vehicles, healthcare wearables, and remote monitoring platforms
  • Highlights emerging technologies including edge computing, blockchain, digital twins, federated AI, and quantum computing for cybersecurity applications
  • Discusses AI-enhanced security automation, threat intelligence, and MITRE ATT&CK-based security mapping within Zero Trust environments
  • Addresses secure telemedicine, remote diagnostics, healthcare data sharing, and medical image management challenges
  • Provides forward-looking perspectives on building resilient, trustworthy, and intelligent urban and healthcare infrastructures

Readership

Cybersecurity researchers and practitioners; Computer scientists specialising in AI and intelligent systems; Smart city architects and urban technology professionals; Healthcare IT and health informatics specialists; IoT, edge computing, and distributed systems researchers; Digital health and telemedicine professionals; Information security managers and technology consultants; Graduate students and advanced academics in cybersecurity, AI, and healthcare technology

Table of contents

1. AI-Powered Smart Cities

2. Foundations of AI-Driven Zero Trust Security in Smart Cities and Healthcare

3. The Evolution of Urban Security from Traditional to AI-Driven Zero Trust Models

4. Integrating AI and Zero Trust for the Future of Smart City Security

5. Building Resilient and Secure Smart Cities with AI and Zero Trust

6. AI and Zero Trust in Autonomous Vehicles for Smart Cities

7. AI for Secure Medical Image Management in Zero Trust Healthcare System

8. AI-Enhanced Security Automation for Smart City IoT Networks with Zero Trust

9. AI and Edge Computing for Securing IoT in Smart Cities and Healthcare

10. AI for Securing Healthcare Wearables and Remote Patient Monitoring Systems

11. AI-Driven MITRE Attack Mapping for Zero Trust Enabled Threat Intelligence

12. Quantum Computing Transforming Healthcare Cybersecurity

13. Emerging AI-Enabled Zero Trust Security for Smart City and Healthcare Applications

14. AI-Enabled Zero Trust Models for Secure Telemedicine and Remote Diagnostics

15. Blockchain-based Healthcare Data Security using Cryptographic Algorithms

16. Digital Twin–Assisted Zero Trust Security: A Framework for Healthcare Data Interoperability

17. TRUST-CHAIN: A Federated AI Trust Scoring Framework with Blockchain-Enforced Zero-Trust Access Control for Healthcare

Product details

  • Edition: 1
  • Latest edition
  • Volume: 146
  • Published: April 1, 2027
  • Language: English

About the editor

Pethuru Raj

Serial Volume Editor

Pethuru Raj, PhD, is the principal AI architect at Infocion Inc., Bangalore. Previously, he worked as the vice president and chief architect at the AI division of Reliance Jio Platforms Ltd., Bangalore, IBM Global Cloud Centre of Excellence, Wipro Consulting Services, and Robert Bosch Corporate Research. He has over 25 years of experience in the IT industry and 9 years of research experience. He completed the CSIR-sponsored PhD at Anna University, Chennai. He conducted UGC-sponsored postdoctoral research in the Department of Computer Science and Automation at the Indian Institute of Science, Bangalore. He focuses on emerging technologies, including Generative and Agentic AI, AI Model Optimization Techniques, Cloud of Things, Cloud-native and Edge Computing Paradigms, Platform Engineering, 6G Communication, and Blockchain Technologies, as well as Quantum-safe Cryptography Algorithms. He has authored and edited over 75 technology books, published more than 60 research papers, and contributed to more than 55 book chapters.

Affiliations and expertise
Principal AI Architect, Infocion Inc., Bangalore, India