Confidential and Private Computing using ORAM and TEE
Yeongjin Jang is an assistant professor of Computer Science at Oregon State University. He hacks a variety of computer systems, from iPhone and CPUs to systems with new technologies such as IoT devices, Blockchain, and automobiles, for analyzing emerging cyber threats on those systems and develop defense mechanisms to counter them.
He holds a B.S. degree from KAIST (2010), an M.S. (2016), and a Ph.D. degree (2017) from Georgia Tech, and won twice in DEF CON CTF (2015 and 2018).
Cloud computing runtimes are unprotected. Unlike data in transit and at rest, which are protected by network/disk encryption, runtime data on DRAM remain unencrypted. Because physical machines are owned by the cloud operator (e.g., AWS), such runtime data are transparently visible to their administrators or attackers who break into the cloud server. This inherent trust problem of ‘outsourced’ cloud computing prohibits the use of cloud in critical operations such as processing confidential data (e.g., government/defense), applying machine learning on medical data (e.g., federated learning), etc.
Many existing approaches to solving this problem are either incomplete or impractical. Trusted execution environments (TEEs), such as Intel SGX and AMD SEV, are fast, however, those techniques are not resistant to side-channel or memory access inference attacks. Fully homomorphic encryption (FHE) and secure multiparty computation (MPC) can provide cryptographic security, however, they are extremely slow to run general computations in the cloud.
This talk introduces a hybrid construction of Trusted Execution Environment (TEE, e.g., Intel SGX) and Oblivious Random Access Machine (ORAM) as a practical solution for securely outsourcing computation in the cloud. Essentially, each technique complements each other in this hybrid construction. Intel SGX, which is fast but not resistant to attacks against memory access patterns, can be protected by ORAM, which is proven to be resistant to such attacks. ORAM, which is secure but much slower than the regular execution, can be speeded up by running its protocol in Intel SGX enclaves. The talk begins with a brief history of SGX+ORAM constructions, presents technical details and recent performance improvements, and ends with demonstrating potential application usages.
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