The purpose of this research is the role of education and preventive protection of vulnerable groups based on neighborhood-based security governance. The research method is applied in terms of its purpose and qualitative in terms of implementation and data-driven approach (grand theory). The statistical population of the research includes 18 participants, including experts in the field of social security and criminology (university professors, urban security researchers), local activists (members of neighborhood social councils, local trustees, civil activists), and officials of executive and law enforcement institutions related to urban security, who were selected using a purposeful snowball sampling method. The data collection tool is semi-structured interviews with experts in the field of social security, local officials, and citizens living in high-risk areas, which continued until theoretical saturation. Grounded data theory was used to analyze the data. The findings show that neighborhood-based security governance with its three main components of "multi-level participation", "neighborhood data-driven management" and "local institutionalization" can provide the basis for active, rapid and effective protection of vulnerable groups. By utilizing neighborhood-based structures, it is possible to support vulnerable groups before crises occur and take action to enhance neighborhood resilience through proactive policymaking.