Computation on Encrypted Data using Dataflow Authentication

• Main Authors: Fischer Andreas, Fuhry Benny, Kerschbaum Florian, Bodden Eric
• Format: Article
• Language: English
• Published: Sciendo 2020-01-01
• Series: Proceedings on Privacy Enhancing Technologies
• Subjects: dataflow authentication; trusted code base; homomorphic encryption; authenticated encryption; secure cloud computing
• Online Access: https://doi.org/10.2478/popets-2020-0002

Encrypting data before sending it to the cloud protects it against attackers, but requires the cloud to compute on encrypted data. Trusted modules, such as SGX enclaves, promise to provide a secure environment in which data can be decrypted and then processed. However, vulnerabilities in the executed program, which becomes part of the trusted code base (TCB), give attackers ample opportunity to execute arbitrary code inside the enclave. This code can modify the dataflow of the program and leak secrets via SGX side-channels. Since any larger code base is rife with vulnerabilities, it is not a good idea to outsource entire programs to SGX enclaves. A secure alternative relying solely on cryptography would be fully homomorphic encryption. However, due to its high computational complexity it is unlikely to be adopted in the near future. Researchers have made several proposals for transforming programs to perform encrypted computations on less powerful encryption schemes. Yet current approaches do not support programs making control-flow decisions based on encrypted data.