Vulnerability to Vigilance

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Authors: Thota Venkat Narayana Rao, C. H. Indu, K. Siva Kumar Gowda, R. Prashanthi
Cited by: 0
References: 4

Abstract

Imagine a world in which all critical infrastructures are safe from threats by defense that learns and adapts itself and is omnipresent. This is the new fad of critical infrastructure security-the future of protection-transforming everything we knew of protecting the life of deep learning innovations. This presents the latest research on implementing deep learning techniques for securing critical infrastructures consisting of power grids, transport systems, and health networks. It has contributions from leading experts, and thus it will delve deep into advancements in deep learning-based anomaly detection, intrusion detection, and threat intelligence. It describes theoretical foundations of deep learning, real and practically running case studies, and scenarios a comprehensive understanding of deep learning in securing critical infrastructure. This chapter focuses on the exploration of latest innovations and applications of future security in critical infrastructures with deep learning

Fields of Study & Subjects

Network Security and Intrusion Detection Adversarial Robustness in Machine Learning Smart Grid Security and Resilience

Publication details

Journal / source
Advances in computational intelligence and robotics book series
Pages
331–352
Publication date
15 January 2026
Document type
Book chapter