Digital Twin based What-if Simulation of Security Attacks in Smart Irrigation Systems

The rapid integration of Internet of Things (IoT), machine learning and big data technologies in smart irrigation systems has significantly enhanced the agricultural efficiency and water resource management. However, it is vital to secure the smart irrigation systems against all types of security attacks. This paper introduces a novel approach, leveraging digital twin technology, for simulating security attacks in smart irrigation systems. Towards achieving this goal, a digital twin, mirroring a physical irrigation system has been built, and a simulation model has been included into it to mimic the perception layer and personal area network attacks. Such a digital twin helps in what-if analysis, to understand the impact of these attacks, on the performance of smart irrigation system. An Amazon Web Services (AWS) based prototype, combining real-time data from sensors with simulation model of the impact of potential security breaches, has been successfully developed. Further, how the digital twin can be used in detecting intrusions, thus enhancing the overall resilience and security of smart irrigation systems, has been presented. This work contributes to the growing field of cybersecurity for IoT applications, specifically addressing the unique challenges posed by the security attacks in smart irrigation.