Security & Privacy

In this era of big data, the privacy of individuals and security of computing systems that handle sensitive data has come to be a central challenge in computer science. At Duke, research in this area has focused on four broad directions:

• Differentially Private Data Science, where researchers at Duke have made fundamental contributions to the theory, algorithms, programming frameworks and systems, and social implications of differential privacy.
• Privacy in Mobile Systems, where the focus at Duke is to study novel architectures for enabling privacy in mobile and smart devices as well as privacy enhancing techniques for sharing sensor data (e.g., camera and location) with potentially malicious applications.
• Oblivious and Secure Computation, where at Duke the goal is to advance the theory and application of cryptographic primitives with the aim of building efficient and practical systems for specific problem domains like graph computation and differentially private analytics.
• Blockchains, where Duke researchers are making foundational contributions to the field of distributed consensus to scale blockchains in a way that achieves robustness without sacrificing low latency and high throughput.