Safeguarding eGovernment Infrastructure from AI-Driven Cyber Attacks

📢 Call for Chapters: Safeguarding eGovernment Infrastructure from AI-Driven Cyber Attacks

We invite academic researchers, cybersecurity analysts, IT practitioners, and public administration scholars to contribute to an upcoming peer-reviewed academic volume, Safeguarding eGovernment Infrastructure from AI-Driven Cyber Attacks, to be published by IGI Global Scientific Publishing (USA) and submitted for indexing in SCOPUS, Clarivate Web of Science (CPCI), and INSPEC.

📖 Introduction

The contemporary digital landscape is undergoing a paradigm shift where Artificial Intelligence (AI) operates simultaneously as an indispensable defense and an unprecedented offensive weapon. The democratization of Generative AI, Large Language Models (LLMs), and autonomous Machine Learning has empowered adversaries to automate spear-phishing at scale, create self-mutating polymorphic malware, orchestrate deepfakes capable of circumventing biometric identity systems, and execute adversarial data poisoning attacks against critical datasets. Traditional static cybersecurity perimeter models are no longer sufficient to counteract dynamic, machine-speed cyber offensives. This edited volume bridges the critical divide between theoretical computer science and operational public-sector IT governance. It delivers actionable frameworks, empirical research, and strategic defense methodologies to protect critical national infrastructure, municipal smart city operations, eGovernment frameworks, and educational repositories against AI-augmented threats.

🎯 Objective

The primary objective of this publication is to provide an authoritative, peer-reviewed reference framework that systematically investigates the dual-use reality of Artificial Intelligence in cyberspace. Specifically, this book aims to:

Analyze Emerging AI-Augmented Threat Vectors: Demystify how threat actors operationalize Generative AI, LLMs, and machine learning algorithms for autonomous reconnaissance, synthetic deception, and automated vulnerability exploitation.
Bridge Theoretical Computer Science and Practical IT Management: Translate complex algorithmic security concepts into actionable strategies, defensive protocols, and technical countermeasures applicable to public-sector and enterprise digital ecosystems.
Safeguard Critical Infrastructure and eGovernment Frameworks: Deliver empirical methodologies and strategic blueprints for fortifying municipal utilities, smart cities, sovereign identity registries, citizen portals, and educational repositories against AI-native breaches.
Evaluate Governance, Legal, and Compliance Standards: Examine international regulatory frameworks (e.g., the EU AI Act, NIST AI Risk Management Framework, ISO/IEC 42001) to provide clear guidance on liability, algorithmic auditing, and digital sovereignty.

👥 Target Audience

Academic Researchers & Scientists: Scholars, postdocs, and university faculty working at the nexus of Cybersecurity, Artificial Intelligence, Machine Learning, Information Systems, and Computer Science.
Cybersecurity Professionals & IT Practitioners: Chief Information Security Officers (CISOs), threat intelligence analysts, penetration testers, Security Operations Center (SOC) engineers, and enterprise security architects.
Public Sector & eGovernment Officials: Digital transformation directors, municipal CIOs, public administration executives, and IT specialists managing smart city networks, citizen registries, and public services.
Policymakers, Regulators, and Legal Experts: National cybersecurity strategists, compliance auditors, and technology policy advisors developing risk mitigation and legislative frameworks for artificial intelligence.
Graduate & Doctoral Students: Master's and PhD students in computer science, software engineering, cybersecurity, and public administration seeking an advanced, research-grade supplementary textbook.

🎯 Recommended Topics

Key themes include, but are not limited to:

1. The Weaponization of Generative AI and LLMs
2. AI-Powered Social Engineering and Automated Phishing
3. Deepfakes: Bypassing Biometric and Identity Verification Systems
4. Machine Learning Vulnerabilities: Adversarial Attacks and Data Poisoning
5. Automated Malware Generation and Polymorphic Viruses
6. AI Threats to eGovernment and Public Sector Digital Infrastructure
7. Securing Academic and Publishing Databases against AI Scraping and Data Breaches
8. Defensive AI: Using Machine Learning for Threat Detection and Anomaly Recognition
9. Regulatory, Legal, and Ethical Frameworks for AI Cybersecurity
10. The Future Horizon: Quantum AI and Next-Generation Cryptography

🔍 Submission Procedure & Guidelines

Researchers and practitioners are invited to submit on or before December 4, 2026, a chapter proposal of 1,000 to 2,000 words clearly explaining the mission and concerns of his or her proposed chapter. Authors will be notified by December 18, 2026 about the status of their proposals and sent chapter guidelines. Full chapters of a minimum of 10,000 words (word count includes references and related readings) are expected to be submitted by March 19, 2027.

All submitted chapters will be reviewed on a double-anonymized review basis.

No Fees: Note: There are no submission or acceptance fees for manuscripts submitted to this book publication, Safeguarding eGovernment Infrastructure from AI-Driven Cyber Attacks.
Formatting: Equations must be formatted using MathType (LaTeX files are NOT compatible with the publisher typesetting system). References must adhere to APA 7th Edition.
Editors: Prof. Dr. Jan Vrba (Akademia Jagiellońska w Toruniu, Poland • e-mail: research@vrba.asia) & Dr. Richard Lightcap, PhD (American National University, USA • e-mail: r_lightcap@hotmail.com).

📅 Important Dates

December 4, 2026: Proposal Submission Deadline
December 18, 2026: Notification of Acceptance
March 19, 2027: Full Chapter Submission
May 21, 2027: Review Results Returned
July 2, 2027: Final Acceptance Notification
July 16, 2027: Final Chapter Submission

🏛️ Publisher & Indexing Information

This book is scheduled to be published by IGI Global Scientific Publishing. This publication is anticipated to be released in 2027. IGI Global Scientific Publishing meets the criteria for inclusion in major indexing services such as Scopus, Clarivate Web of Science (CPCI), and INSPEC.

🔗 Online Submission Portal

Proposals and manuscripts must be submitted directly through IGI Global's official eEditorial Discovery platform:
Submit Chapter Proposal via IGI Global Portal →

Official IGI Global Call Details: https://www.igi-global.com/publish/call-for-papers/call-details/10414

Official CFP / External Details → Submit Inquiry / Propose Paper →