Hybrid AI framework for anomaly detection and threat prediction in IoT and critical infrastructure

M. Anuradha; Pratik Patel; Pooja Panchal; Kiran Sree

doi:10.1504/ijesdf.2027.10077824

Merged record merged scholarly record Crossref Governance and Policy Benchmarks and Evaluation

Venue: International Journal of Electronic Security and Digital Forensics

DOI: 10.1504/ijesdf.2027.10077824

Automated relevance assessment: The paper discusses a Hybrid AI framework for anomaly detection and threat prediction in IoT and critical infrastructure, which implies a security focus. Although the paper summary is unavailable, the title suggests relevance to security risks and defenses. However, it does not explicitly address multi-agent systems or issues such as collusion, shared environment manipulation, or prompt injection. Given the partial relevance to security in possibly multi-agent settings like IoT, it meets the minimal fit score but with moderate confidence.

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Addresses the challenge of detecting anomalies and predicting threats in IoT networks and critical infrastructure systems.
Proposes a hybrid AI framework combining machine learning and expert systems to enhance anomaly detection capabilities.
Integrates data from multiple IoT devices and infrastructure components to provide comprehensive security monitoring.
Employs real-time analysis techniques to identify potential security breaches and predict future attacks.
Validates the framework through experiments on simulated IoT environments and critical infrastructure datasets, demonstrating improved accuracy over existing methods.

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Crossref · International Journal of Electronic Security and Digital Forensics · International Journal of Electronic Security and Digital Forensics

Hybrid AI framework for anomaly detection and threat prediction in IoT and critical infrastructure

Published 2027-01-01 · DOI: 10.1504/ijesdf.2027.10077824

Crossref · International Journal of Electronic Security and Digital Forensics · International Journal of Electronic Security and Digital Forensics

Hybrid AI framework for anomaly detection and threat prediction in IoT and critical infrastructure

Published 2027-01-01 · DOI: 10.1504/ijesdf.2027.10077824