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In the current technological landscape, Internet of Things (IoT) systems are deeply embedded in numerous facets of daily life, from domestic settings to critical infrastructure, which underscores the importance of these systems security and integrity. The constrained nature of IoT devices, in terms of computational capacity, economic limitations, or time-to-market, makes them vulnerable to security breaches and system failures. Additionally, the hybrid essence of IoT- combining the physical domain via sensor interfaces and the cyber domain through communication networks and cloud connectivity- further complicates mitigating these threats. While numerous techniques for either network intrusion detection or sensor anomaly detection exist, an integrated approach that synergistically combines information from both domains is absent. This paper proposes a multi-modal data fusion technique, which, for the first time …