Editor: S M Nazmuz Sakib
Publisher: Springer (To be submitted for SCOPUS Indexing)
Publisher: Springer (To be submitted for SCOPUS Indexing)
Introduction
As the proliferation of Internet of Things (IoT) devices and edge computing environments continues to accelerate, securing these distributed infrastructures has become a paramount challenge. Traditional centralized security frameworks are increasingly inadequate for handling the massive volume, low latency, and resource-constrained nature of edge environments. To address these emerging vulnerabilities, this upcoming peer-reviewed scholarly volume, "Intelligent Edge Security: AI-Driven Malware Defense and Decentralized Architectures," aims to bring together cutting-edge research at the intersection of Artificial Intelligence, decentralized systems, and edge computing.
This volume will explore advanced methodologies to fortify edge nodes against sophisticated cyber threats. By focusing on AI-driven malware detection, zero-trust architectures, and decentralized cryptographic frameworks like blockchain, the book provides a comprehensive roadmap for building self-adaptive, privacy-preserving, and resilient security systems. We welcome high-quality, original, and unpublished book chapters from global researchers, academicians, and industry experts that propose innovative frameworks, theoretical models, or empirical studies addressing these vital themes.
Key Themes & Topics of Interest
Contributors are invited to submit chapters on topics including, but not limited to:
- AI-driven malware detection and real-time threat detection at the edge
- Edge computing, IoT, and Internet of Medical Things (IoMT) security frameworks
- Blockchain, smart contracts, and decentralized cryptographic systems
- Generative AI models and federated learning for distributed security
- Hardware security, sensor-based systems, and cyber-physical monitoring
- Zero-trust, self-adaptive network architectures, and privacy-preserving computation
- Adversarial robustness, fuzzy logic, and category theory in security modeling
Submission Guidelines
- All manuscripts must consist of original, unpublished work.
- Formatting must strictly adhere to the IEEE reference and citation style.
- Submissions must include the Chapter Title, Author Name(s), Affiliation, Country, Email, H-index, and Scopus Profile link.
- Authors must submit the full manuscript along with a Turnitin Plagiarism & AI Report (a formal non-AI content declaration is required).
For submissions and inquiries, please contact the editor at sakibpedia@gmail.com.