Kim Wuyts discusses her work in privacy threat modeling with LINDDUN, a framework inspired by Microsoft's STRIDE for security threat modeling. LINDDUN provides a structure to analyze privacy threats across multiple categories such as linking, detecting data disclosure, and unawareness. The framework has been updated over the years to incorporate new knowledge and developments in privacy, and it has become recognized as a go-to approach for privacy threat modeling.

Kim believes that privacy and security can be combined and highlights the importance of protecting individuals' rights and data while securing systems and assets.

Privacy by design, which focuses on reducing unnecessary data collection and considering individual needs, is discussed in relation to secure architecture and threat modeling. The Threat Modeling Manifesto is emphasized as a significant resource for promoting privacy threat modeling. 

Kim addresses emerging trends in privacy, including the concerns surrounding AI and responsible AI, and stresses the need for increased awareness among individuals and companies about privacy issues and the importance of privacy protection.

Listen in as Kim explains the importance of collaboration between security and privacy teams, integrating privacy into security practices, and recognizing the value of privacy for both privacy protection and overall security.

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