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Cyber-Physical Security in IoT-Enabled Autonomous Defense Systems: Threat Modeling and Response
Subject area: Science,Engineering and Technology · Area of research: Stevens Institute of Technology, Hoboken NJ
Abstract
The convergence of Internet of Things (IoT) technologies with autonomous defense systems has created sophisticated cyber-physical systems (CPS) that present both unprecedented capabilities and unique security challenges. This paper provides a comprehensive analysis of cybersecurity threats, vulnerabilities, and defense mechanisms in IoT-enabled autonomous defense systems. We examine threat modeling approaches, explore adaptive defense strategies, and evaluate the role of emerging technologies such as digital twins and artificial intelligence in enhancing system security. Through systematic analysis of current literature and empirical evidence, this research contributes to the understanding of security paradigms necessary for protecting critical autonomous defense infrastructure against evolving cyber threats.
Keywords
Cyber-Physical Systems, IoT Security, Autonomous Defense, Threat Modeling, Adaptive Security
How to cite this paper
@article{1710451,
author = {Nicholas Tetteh Ofoe, Joy Selasi Agbesi},
title = {Cyber-Physical Security in IoT-Enabled Autonomous Defense Systems: Threat Modeling and Response},
journal = {Iconic Research And Engineering Journals},
year = {2025},
volume = {9},
number = {3},
pages = {110-120},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1710451.pdf},
abstract = {The convergence of Internet of Things (IoT) technologies with autonomous defense systems has created sophisticated cyber-physical systems (CPS) that present both unprecedented capabilities and unique security challenges. This paper provides a comprehensive analysis of cybersecurity threats, vulnerabilities, and defense mechanisms in IoT-enabled autonomous defense systems. We examine threat modeling approaches, explore adaptive defense strategies, and evaluate the role of emerging technologies such as digital twins and artificial intelligence in enhancing system security. Through systematic analysis of current literature and empirical evidence, this research contributes to the understanding of security paradigms necessary for protecting critical autonomous defense infrastructure against evolving cyber threats.},
keywords = {Cyber-Physical Systems, IoT Security, Autonomous Defense, Threat Modeling, Adaptive Security},
month = {September},
}