End-to-End Collection and Analysis of Multi-Level Heterogeneous Data with IoT Security Using Novel Encrypted Code in Parallel Processing

Abstract

The Internet of Things (IoT) networks are increasingly prevalent across various domains, necessitating robust security monitoring due to the need to process vast amounts of heterogeneous data in real-time. Addressing this challenge requires the implementation of a parallel system for on-the-fly security data processing, leveraging complex event processing (CEP) technology. This analysis introduces a scalable and configurable infrastructure designed for the collection and processing of security-related datasets from IoT systems and devices. Key to enabling such approaches is the development of infrastructures capable of handling large-scale data collection, streaming, and storage. The proposed infrastructure facilitates the collection of security data from diverse IoT components, including individual devices, smart objects, edge nodes, IoT platforms, and cloud enzironments. The scalability of this infrastructure is achieved through the integration of cutting-edge technologies for large-scale data handling, while its configurability is ensured through an extensible approach to modeling security data from various IoT systems and devices. This enables the instantiation and deployment of security data collection systems in complex IoT environments, laying the groundwork for the application of advanced security analytics algorithms aimed at identifying threats, vulnerabilities, and attack patterns.