Sasy, Sajin2017-12-122017-12-122017-12-122017-11-28http://hdl.handle.net/10012/12700We are witnessing a confluence between applied cryptography and secure hardware systems in enabling secure cloud computing. On one hand, work in applied cryptography has enabled efficient, oblivious data-structures and memory primitives. On the other, secure hardware and the emergence of Intel SGX has enabled a low-overhead and mass market mechanism for isolated execution. By themselves these technologies have their disadvantages. Oblivious memory primitives carry high performance overheads, especially when run non-interactively. Intel SGX, while more efficient, suffers from numerous software-based side-channel attacks, high context switching costs, and bounded memory size. In this work we build a new library of oblivious memory primitives, which we call ZeroTrace. ZeroTrace is designed to carefully combine state-of-art oblivious RAM techniques and SGX, while mitigating individual disadvantages of these technologies. To the best of our knowledge, ZeroTrace represents the first oblivious memory primitives running on a real secure hardware platform. ZeroTrace simultaneously enables a dramatic speedup over pure cryptography and protection from software-based side-channel attacks. The core of our design is an efficient and flexible block-level memory controller that provides oblivious execution against any active software adversary, and across asynchronous SGX enclave terminations. Performance-wise, the memory controller can service requests for 4~Byte blocks in 1.2~ms and 1~KB blocks in 3.4~ms (given a 10~GB dataset). On top of our memory controller, we evaluate Set/Dictionary/List interfaces which can all perform basic operations (e.g., get/put/insert) in 1-5~ms for a 4-8~Byte block size. ZeroTrace enables secure remote computations at substantially lower overheads than other comparable state-of-the-art techniques.enImplementationCloud SecurityComputing on Encrypted DataOblivious PrimitivesMaster Thesis