Security and privacy in Local Digital Twins (LDTs) are vital as these systems handle sensitive data from various sources. If compromised, it can lead to significant operational disruptions, loss of public trust, and safety hazards. Existing EU frameworks, like the GDPR and NIS2 Directive, provide guidelines, but proactive security and privacy measures are essential. Utilizing proactive, anticipatory approaches, such as the Triple Loop Learning framework, this unit equips participants to transition from reactive to strategic security thinking. Key measures include threat modeling, security audits, and embracing privacy-by-design techniques to prevent unauthorized data access and usage while ensuring compliance with regulations. This learning unit builds upon previous modules, focusing on embedding security within data flow processes of LDTs. Through practical applications and anticipatory risk management strategies, participants learn to safeguard against threats and prepare for emerging risks, while fostering an environment of trust and collaboration for future scalable LDT solutions.