Towards the Deployment of Secure Computation Tools in Genomics: A Sociotechnical Perspective

The genomics community faces an increasing demand to leverage private data across institutional boundaries. Secure computation technologies, encompassing both trusted execution environments (TEEs) and secure multiparty computation (MPC) frameworks, promise to allow collaborative analysis while overcoming privacy concerns associated with genomic data sharing. However, discrepancies between real-world security needs and what these technologies provide present a key hurdle in deployment efforts. In this talk, I will present ideas for addressing this challenge from both technical and societal perspectives. First, I will describe our recent work on privacy-preserving genotype imputation using Intel SGX, which introduces new algorithmic strategies to provide resilience to side-channel vulnerabilities. Second, I will discuss an apparent disconnect in contextual norms and values between the conventional security models versus real-world settings in genomics. I will illustrate an alternative trust-based framework aimed at better aligning the tools with the institutional trust landscape and interests of human subjects. A sociotechnical design of privacy tools is crucial for realizing their potential in genomics.