Digital Twin-Driven Cyber Deception and Intelligent Adversary Modeling for Securing Hybrid Enterprise Cloud Environments
DOI:
https://doi.org/10.15662/IJEETR.2026.0806002Keywords:
Digital twin, cyber deception, intelligent adversary modelling, hybrid cloud security, cybersecurity, machine learning, threat intelligence, deception technology, adversarial behaviour analysis, enterprise cloud infrastructureAbstract
The increasing adoption of hybrid enterprise cloud environments has introduced complex cybersecurity challenges due to the integration of on-premises infrastructure, public cloud platforms, private clouds, virtual machines, and distributed enterprise applications. Traditional security mechanisms primarily depend on perimeter protection, intrusion detection, and reactive incident response, which may be insufficient against sophisticated adversaries employing adaptive attack strategies. Digital twin-driven cyber deception offers an emerging approach by creating virtual representations of enterprise infrastructure that enable controlled threat observation, adversary behaviour analysis, and proactive security assessment. This research proposes an intelligent cybersecurity framework integrating digital twin technology, cyber deception mechanisms, and adversary modelling to strengthen the security of hybrid enterprise cloud environments. The proposed framework incorporates virtualized infrastructure representations, behavioural analytics, machine learning algorithms, and deception-based monitoring to identify suspicious activities and understand potential adversarial strategies. Intelligent adversary modelling is used to analyse attack characteristics, predict behavioural patterns, and evaluate potential security threats within simulated enterprise environments. Furthermore, digital twins provide a controlled environment for evaluating defensive strategies without directly affecting operational infrastructure. The research aims to improve threat detection accuracy, enhance situational awareness, and support proactive cybersecurity decision-making. The proposed approach establishes a foundation for adaptive, scalable, and intelligence-driven security management across interconnected hybrid cloud infrastructures.
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