Dual-Channel Multi-Level Model for Quantitative Assessment of Data Security in Corporate Networks

Modern corporate networks operate in increasingly complex and heterogeneous environments, which complicates the objective assessment of their current security state. This study proposes a dual-channel multi-level model for quantitative assessment of data security in corporate networks using a predefined list of indicators aligned with international cybersecurity standards. The model combines two analytical channels: compliance with security requirements and policies and absence of signs of compromise. Indicator values are normalized and successively aggregated to the levels of confidentiality, integrity and availability aspects; then to node-level scores; and finally to integrated network-level assessments, taking into account node criticality weights. The model was evaluated in a simulation environment using a 14-day scenario with four phases, including normal operation, controlled degradation of security-related indicators, partial recovery and active compromise of a critical node. The results showed that the proposed approach can distinguish between different types of security degradation, localize problematic nodes, identify the most affected security aspects and reveal the indicators responsible for the decline in integrated scores. A comparison with a simplified direct averaging approach was used as an analytical baseline to illustrate the difference between compensatory and non-compensatory channel integration under identical input data and scenario conditions. The results should therefore be interpreted as a controlled numerical demonstration of the model’s aggregation behavior rather than as a complete empirical validation against external cybersecurity assessment frameworks. The proposed model can serve as a basis for analytical security assessment and decision support in corporate networks.