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README.md

SMCQL : Secure Querying for Federated Databases


Author

SMCQL is developed and currently maintained by Johes Bater, under the direction of Jennie Rogers. It translates SQL statements into ObliVM programs for secure query evaluation.


Disclaimer

The code is a research-quality proof of concept, and is still under development for more features and bug-fixing.


Requirements

  • PostgreSQL 9.5+
  • Apache Calcite 1.8+
  • Apache Maven 3+
  • Oracle Java 8+
  • JavaCC 5.0+
  • Python 2.7+

Setup

Clone the repository:

$ git clone https://github.com/smcql/smcql.git

Install the dependencies as needed:

  • Install PostgreSQL:

    $ sudo apt-get install postgresql postgresql-contrib

  • Create a superuser PostgreSQL role for SMCQL:

    $ sudo su - postgres
    $ createuser -sPE smcql
    $ exit

  • Install Maven:

    $ sudo apt-get install maven

  • Install Java:

    $ sudo apt-get install default-jdk

Edit the configuration files as needed:

  • conf/setup.localhost
  • conf/connections/localhost

This configures your local environment for SMCQL. Note that you should insert your PostgreSQL password for SMCQL here. You also may want to add setup.localhost to your .gitignore to avoid pushing your password.

Start up PostgreSQL and run the following command in the SMCQL home directory:

$ ./setup.sh

This sets up the test databases in PostgreSQL.


Running the example queries

Run the following commands for the respective queries:

Query 1: Comorbidity
$ ./build_and_execute.sh conf/workload/sql/comorbidity.sql testDB1 testDB2 

Query 2: Aspirin Count
$ ./build_and_execute.sh conf/workload/sql/aspirin-count.sql testDB1 testDB2

Query 3: Recurrent C.Diff
$ ./build_and_execute.sh conf/workload/sql/cdiff.sql testDB1 testDB2 

Note that these queries are CPU-intensive. They may take several minutes to run, depending on hardware.


Running SMCQL with your own data and schema

Refer to conf/workload/testDB for the necessary files:

  1. create_test_dbs.sh - This script creates and populates the PostgreSQL databases that house the data
  2. test_schema.sql - This SQL query sets the schema, as well as the security level for each attribute

The above files are an automated example for setting up the test databases and annotated schema. You can choose to set these up manually, or to use existing databases. Please note that you must set the security levels for your attributes. Look at the bottom of test_schema.sql for an example. Remember that each attribute must be set as either a public, protected, or private variable.


Running the example queries on different machines

  1. Create new configuration files for your remote hosts:
  • conf/setup.remote
  • conf/connections/remote-hosts
  1. Ensure that you have three machines with direct ssh access to one another.

  2. Populate two of the machines with your data, in their local PostgreSQL instances. These will be your two workers, so each will have their own data.

  3. Make sure that both your workers have their schemas set correctly (as detailed in the previous section). Remember that the schemas, and security annotations, must be the same for both machines.

  4. On the third machine (the honest broker), ensure that you have a copy of the repository and that the configuration files are populated with the correct worker configuration information.

  5. Run the example command on the honest broker, from the SMCQL repository:

    $ ./build_and_execute.sh conf/workload/sql/comorbidity.sql remoteDB1 remoteDB2

Notes:

  • Machine 1: Contains PostgreSQL database 'remoteDB1' and correct schema
  • Machine 2: Contains PostgreSQL database 'remoteDB2' and correct schema
  • Machine 3: Contains configuration files that specify the locations and connection information for 'remoteDB1' and 'remoteDB2'

References

SMCQL:

J. Bater, G. Elliott, C. Eggen, S. Goel, A. Kho, and J. Rogers, “SMCQL: Secure Querying for Federated Databases.”, VLDB, 10(6), pages 673-684, 2017.

ObliVM:

C. Liu, X. S. Wang, K. Nayak, Y. Huang, and E. Shi, “ObliVM : A Programming Framework for Secure Computation,” Oakland, pp. 359–376, 2015.


Notes

See slides presented at VLDB 2017 for more details.