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With the rapid growth in popularity of Digital Twins (DTs), there is a pressing need to ensure data integrity within Internet of Things (IoT) systems. The complexity of potential anomalies in Internet of Things (IoT) data requires mechanisms that can evaluate these behaviors and understands them in advance without disrupting live systems. DTs offer a solution by replicating physical systems in a virtual environment, allowing new functionalities like monitoring, optimization, and prediction. To improve these functionalities, cognitive capabilities are encompassed, leading to the emergence of Cognitive Digital Twin (CDT). The findings of this research underscore the transformative impact of CDTs in strengthening IoT system security, realized by harnessing the capabilities of cognitive technologies and the additional layer of data generation that introduce the new framework “Cognitive Super Digital Twin” (CSDT).

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Enhancing Data Integrity with CSDT: A Solution to Predict Data Disturbance in IoT Systems

  • 会议论文

  • 发表日期：

    2025年

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  • Meriem Smati,
  • Jannik Laval,
  • Vincent Cheutet,
  • Christophe Danjou

摘要

With the rapid growth in popularity of Digital Twins (DTs), there is a pressing need to ensure data integrity within Internet of Things (IoT) systems. The complexity of potential anomalies in Internet of Things (IoT) data requires mechanisms that can evaluate these behaviors and understands them in advance without disrupting live systems. DTs offer a solution by replicating physical systems in a virtual environment, allowing new functionalities like monitoring, optimization, and prediction. To improve these functionalities, cognitive capabilities are encompassed, leading to the emergence of Cognitive Digital Twin (CDT). The findings of this research underscore the transformative impact of CDTs in strengthening IoT system security, realized by harnessing the capabilities of cognitive technologies and the additional layer of data generation that introduce the new framework “Cognitive Super Digital Twin” (CSDT).