Redefining genomic privacy: trust and empowerment

Current models of protecting human subjects create a zero-sum game of privacy versus data utility. We propose shifting the paradigm to techniques that facilitate trust between researchers and participants.

Fulfilling the promise of the genetic revolution requires the analysis of large datasets containing information from thousands to millions of participants. However, sharing human genomic data requires protecting subjects from potential harm. Current models rely on de-identification techniques in which privacy versus data utility becomes a zero-sum game. Instead, we propose the use of trust-enabling techniques to create a solution in which researchers and participants both win. To do so we introduce three principles that facilitate trust in genetic research and outline one possible framework built upon those principles. Our hope is that such trust-centric frameworks provide a sustainable solution that reconciles genetic privacy with data sharing and facilitates genetic research.

Cloud control with distributed rate limiting

Today's cloud-based services integrate globally distributed resources into seamless computing platforms. Provisioning and accounting for the resource usage of these Internet-scale applications presents a challenging technical problem. This paper presents the design and implementation of distributed rate limiters, which work together to enforce a global rate limit across traffic aggregates at multiple sites, enabling the coordinated policing of a cloud-based service's network traffic. Our abstraction not only enforces a global limit, but also ensures that congestion-responsive transport-layer flows behave as if they traversed a single, shared limiter. We present two designs - one general purpose, and one optimized for TCP - that allow service operators to explicitly trade off between communication costs and system accuracy, efficiency, and scalability. Both designs are capable of rate limiting thousands of flows with negligible overhead (less than 3% in the tested configuration). We demonstrate that our TCP-centric design is scalable to hundreds of nodes while robust to both loss and communication delay, making it practical for deployment in nationwide service providers.