A comprehensive approach to building an intelligent system for proactive personnel risk assessment in critical infrastructure

Modern challenges in organizational security, particularly within critical infrastructure sectors (energy, transportation, finance, IT), necessitate innovative solutions to mitigate risks associated with hiring unreliable personnel. This requires a shift from conducting fragmented checks to the creation and implementation of comprehensive systems for proactive risk assessment. The urgency of developing such systems is driven by the high frequency and catastrophic consequences of insider incidents, coupled with the inability of traditional methods to detect complex, multi-stage threats originating from employees. However, building intelligent systems that semantically integrate heterogeneous data (biographical, behavioral, financial, digital) presents new systemic challenges. The aim of this article is to analyze the key methodological, ethical-legal, and architectural requirements for designing such systems. The work sequentially examines: 1) ethical and legal dilemmas (fairness, privacy, the right to explanation) and the constraints imposed by personal data legislation; 2) specific cyber threats targeting the compromise of the knowledge base and system logic, along with architectural countermeasures based on Security by Design principles; 3) a comparative analysis of the technological components of a multi-level assessment system (documentary verification, psychometric testing, AI analysis), justifying the necessity for their integration. The scientific novelty lies in a synthetic approach that forms a holistic methodology, considering not only technological efficiency but also fundamental legal constraints and information security requirements. The practical significance of the work consists in formulating systemic requirements for the design of secure, lawful, and socially responsible intelligent decision support systems for personnel security.