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The rapid proliferation of Internet of Things (IoT) devices has introduced unprecedented security challenges for critical infrastructure systems. Honeypots and honeynets have emerged as promising deception technologies for detecting, deflecting, and investigating IoT-specific threats. In this paper, we propose an integrated framework for the design, implementation, and evaluation of adaptive honeypots in IoT environments. The framework consists of two key components: (1) an adaptive honeypot architecture that dynamically adjusts its behaviour based on observed attack patterns and (2) an evaluation methodology with quantitative metrics to assess the effectiveness of IoT honeypots. We discuss the current usage and future potential of this integrated framework in the context of critical infrastructure protection, highlighting challenges and opportunities for collaborative defence against evolving cyber threats.

The research paper outlines the problem of organization collaboration of users group on creation distance learning courses. The article contains analysis of the courses data structure. According to proposed structure the model of developer’s collaboration on creating distance learning courses based on basic principles of source code management was proposed. The article also provides result of research on necessary tools for collaborative development of courses in distance learning platforms. According to the requirements of flexibility and simplicity of access to system for any level educational institutions, technological decisions on granting permissions on performing basic operations on course elements and providing to user moderation’s privileges were proposed.