Studies on security and privacy of genomic data

Abstract

The digital age has ushered in a heightened awareness of privacy concerns, yet systematic methods to address privacy threats in software-based systems are still lacking. To bridge this gap, we introduce a comprehensive framework tailored for modeling privacy threats with precision. Drawing inspiration from established models like STRIDE, our framework using Lindunn methodology employs an information flow-oriented approach to guide analysts in identifying and mapping privacy threats to system elements. We provide a detailed catalog of privacy-specific threat tree patterns to enhance threat analysis, facilitating a nuanced understanding of potential risks. Additionally, our framework simplifies the selection of privacy-enhancing technologies (PETs) by offering guidance on mapping these technologies to identified threats, streamlining the process of privacy requirements elicitation and fulfillment within software systems. Through these contributions, our framework aims to bolster privacy protection efforts and promote trust in digital environments.