Abstract

Networks of the Internet of Things (IoT) nowadays find greater widespread in many domains. Particularities of creation of IoT make the problem of their security monitoring rather actual; it is caused by necessity of processing of big amounts of heterogeneous data in real time. The problem may be solved by means of implementation of the parallel system for security data processing within IoT on the fly basing on complex event processing (CEP) technology. A key prerequisite for enabling such approaches is the development of scalable infrastructures for collecting and processing security-related datasets from IoT systems and devices. This analysis introduces such a scalable and configurable data collection infrastructure for data-driven IoT security. It emphasizes the collection of (security) data from different elements of IoT systems, including individual devices and smart objects, edge nodes, IoT platforms, and entire clouds. The scalability of the introduced infrastructure stems from the integration of state of the art technologies for large scale data collection, streaming and storage, while its configurability relies on an extensible approach to modelling security data from a variety of IoT systems and devices. The approach enables the instantiation and deployment of security data collection systems over complex IoT deployments, which is a foundation for applying effective security analytics algorithms towards identifying threats, vulnerabilities and related attack patterns.

Description