SECURING IOT AND MOBILE CONVERGENCE WITH IOTMOBILESYNC-XGBOOST: A HIGH-PERFORMANCE PROTOCOL FOR SEAMLESS AND SECURE DATA INTEGRATION
Keywords:
Security, IoTMobileSync, XGBoost, Data Integration, Hybrid Algorithm, IoT And Mobile Networks, Machine Learning Security, Mobile-IoT EcosystemsAbstract
The integration of Internet of Things (IoT) devices with mobile platforms introduces significant security challenges, necessitating robust, efficient protocols for data transmission. This paper presents IoTMobileSync-XGBoost, a novel hybrid security and synchronization protocol that combines machine learning-driven threat detection with optimized data management techniques. The proposed method integrates the XGBoost model for real-time prediction of synchronization times and anomaly detection, dynamically predicting and mitigating potential security threats with an impressive 96% accuracy in threat identification. Additionally, the protocol employs adaptive end-to-end encryption and secure key exchange mechanisms to ensure the integrity and confidentiality of transmitted data. Experimental results reveal a 44% reduction in average synchronization time and a 35% decrease in encryption overhead compared to traditional methods, significantly enhancing the efficiency of IoT-mobile interactions. The system also supports scalability, effectively managing up to 10,000 devices while maintaining low latency during peak traffic. These findings demonstrate that IoTMobileSync-XGBoost offers a comprehensive solution for secure and efficient data synchronization, making it suitable for real-time, scalable IoT-mobile integrations across various applications.
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Copyright (c) 2024 Diwakar Reddy Peddinti, Sriram Santosh Aripirala, Pranay Airan (Author)
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