Cuttlefish is a system that makes Partial Homomorphic Encryption practical. Cuttlefish uses the abstraction of Secure Data Types to enable a set of compilation techniques and efficiently compute data analytics queries in public cloud infrastructures while keeping sensitive data confidential. In cases where Partial Homomorphic Encryption (PHE) is not expressive enough to execute a query, Cuttlefish resorts to client-side completion, client-side re-encryption, or secure hardware-based re-encryption based on Intel’s SGX when available.
This project is based on our SoCC 2017 paper.
Savvas Savvides, Julian Stephen, Masoud Saeida Ardekani, Vinai Sundaram, Patrick Eugster
Secure data types: a simple abstraction for confidentiality-preserving data analytics
SoCC '17 Proceedings of the 2017 Symposium on Cloud Computing
Santa Clara, California — September 24 - 27, 2017
This repo includes an example evaluation of TPC-H using Cuttlefish that compares the plaintext execution to the PHE execution.
Installation
First download the Cuttlefish codebase and set the environment variable CUTTLEFISH_HOME to point
to the top directory of this repo.
Cuttlefish is built on top of Apache Spark. Install Spark and set the environmental
variable SPARK_HOME to point to the Spark installation.
With maven installed in your system, run the script:
./scripts/setup.sh
Usage
First generate the TPC-H tables using:
./scripts/loadTables.sh
Then you can execute all 22 TPC-H queries in plaintext mode with:
./scripts/runPtxt.sh
and in PHE mode using:
./scripts/runPhe.sh
Contact
If you want to know more about our project or have questions, please contact Savvas savvas@purdue.edu.