The rapid expansion of the Internet of Things (IoT)
has introduced significant security challenges that traditional
Security Operations Centers (SOCs) are not fully equipped
to handle. This research aims to develop a comprehensive
architecture that addresses currently identified but untreated
specificities in IoT environments. The primary focus is on defining
a generic and scalable model for retrieving and processing data,
considering the heterogeneous nature and constraints of IoT
systems, as this is foundational for building a SOC capable
of managing the complexities of a diverse IoT environment.
This model will take into account for protocol diversity, data
variety and representations, low energy requirements, connected/
disconnected modes, the potential for physical reactions, and the
need for both active and passive monitoring. Subsequently, the
research will explore storage and visualization models tailored
to these heterogeneous environments. One innovative approach
involves coupling Blockchain technology, which offers decentral-
ization and data integrity, with a time-series database for efficient
querying and ease of visualization. Additionally, the research will
focus on implementing automatic and generic penetration tests
specifically designed for heterogeneous IoT systems. These tests
will identify potential vulnerabilities, enable preventive security
measures, and test the robustness of the proposed architecture.
In summary, this research will address critical security aspects in
IoT environments by enhancing monitoring, data analysis, and
threat responsiveness, and by incorporating penetration tests to
bolster system resilience.