From 422a57313266c2bd9a6e0db7870475d8e4d5228f Mon Sep 17 00:00:00 2001
From: Eric Enzler <92583189+ETHenzlere@users.noreply.github.com>
Date: Mon, 17 Jun 2024 20:19:15 +0200
Subject: [PATCH] Feat: Add Skeleton to support Dataset anonymization with
differential privacy (#455)
**DP-Anonymization for BenchBase**
In order to measure the influence of modern anonymization techniques on
datasets and their query performance, we would like to add support for
differential privacy mechanisms to BenchBase. In this PR, we have added
the skeleton of our approach to the codebase. We would like to introduce
a new flag: `--anonymize=true` to the system that allows to anonymize
tables after the loading step and before execution.
The anonymization will:
1. Pull data from the DBMS via already specified JDBC connection
(config)
2. Run DP-algorithms on the data to create a new, synthetic dataset
3. Push the synthetic data back to the DBMS as an anonymized copy
The anonymization information must be provided in the config file. The
process will work with minimal information but also allow for
fine-tuning. A separate README file has been constructed that will list
all the features and how to use them.
`/scripts/anonymization/README.md`
Minimal config:
```
```
Sensitive value handling is one feature we want to add to the process
immediately. It replaces actual values of specified columns with fake
ones. The code base has already been written, tested and used privately
within BenchBase.
The column faking approach will be decoupled from differential privacy,
to allow for more control.
```
```
**Disclaimer: The anonymization itself is not part of this PR in order
to reduce the complexity. Currently, the anonymization flag will call
the script and parse the config. The rest of the code is
ready-to-be-added**
[Architecture
Benchbase.pdf](https://github.com/cmu-db/benchbase/files/14356135/Architecture.Benchbase.pdf)
---------
Co-authored-by: Brian Kroth
---
.github/workflows/maven.yml | 25 +-
.github/workflows/python.yml | 34 ++
.gitignore | 5 +-
.pylintrc | 45 +++
config/mysql/sample_anonymization_config.xml | 42 +++
scripts/anonymization/README.md | 352 ++++++++++++++++++
scripts/anonymization/architecture.png | Bin 0 -> 429837 bytes
scripts/anonymization/requirements.txt | 11 +
scripts/anonymization/src/anonymizer.py | 107 ++++++
.../src/configuration/config_parser.py | 118 ++++++
.../src/configuration/configurations.py | 136 +++++++
.../anonymization/src/modules/jdbc_handler.py | 152 ++++++++
scripts/anonymization/src/test.py | 74 ++++
.../java/com/oltpbenchmark/DBWorkload.java | 53 +++
14 files changed, 1152 insertions(+), 2 deletions(-)
create mode 100644 .github/workflows/python.yml
create mode 100644 .pylintrc
create mode 100644 config/mysql/sample_anonymization_config.xml
create mode 100644 scripts/anonymization/README.md
create mode 100644 scripts/anonymization/architecture.png
create mode 100644 scripts/anonymization/requirements.txt
create mode 100644 scripts/anonymization/src/anonymizer.py
create mode 100644 scripts/anonymization/src/configuration/config_parser.py
create mode 100644 scripts/anonymization/src/configuration/configurations.py
create mode 100644 scripts/anonymization/src/modules/jdbc_handler.py
create mode 100644 scripts/anonymization/src/test.py
diff --git a/.github/workflows/maven.yml b/.github/workflows/maven.yml
index f3911d957..d3c4fa4a8 100644
--- a/.github/workflows/maven.yml
+++ b/.github/workflows/maven.yml
@@ -35,6 +35,7 @@ env:
POM_VERSION: 2023-SNAPSHOT
JAVA_VERSION: 21
ERRORS_THRESHOLD: 0.01
+ PYTHON_VERSION: "3.10"
concurrency:
group: ${{ github.workflow }}-${{ github.ref }}-${{ github.event_name }}
@@ -265,7 +266,7 @@ jobs:
strategy:
fail-fast: false
matrix:
- benchmark: [ 'auctionmark', 'chbenchmark', 'epinions', 'hyadapt', 'noop', 'otmetrics', 'resourcestresser', 'seats', 'sibench', 'smallbank', 'tatp', 'templated', 'tpcc', 'tpcc-with-reconnects', 'tpch', 'twitter', 'voter', 'wikipedia', 'ycsb' ]
+ benchmark: [ 'anonymization', 'auctionmark', 'chbenchmark', 'epinions', 'hyadapt', 'noop', 'otmetrics', 'resourcestresser', 'seats', 'sibench', 'smallbank', 'tatp', 'templated', 'tpcc', 'tpcc-with-reconnects', 'tpch', 'twitter', 'voter', 'wikipedia', 'ycsb' ]
services:
mysql: # https://hub.docker.com/_/mysql
image: mysql:latest
@@ -301,6 +302,21 @@ jobs:
java-version: ${{env.JAVA_VERSION}}
distribution: 'temurin'
+ - name: Set up Python
+ uses: actions/setup-python@v4
+ with:
+ python-version: ${{env.PYTHON_VERSION}}
+
+ - name: Install Python dependencies
+ working-directory: ./scripts/anonymization
+ run: |
+ if [[ ${{matrix.benchmark}} == anonymization ]]; then
+ python -m pip install --upgrade pip
+ pip install -r requirements.txt
+ else
+ echo "Dependency installation not necessary for benchmark"
+ fi
+
- name: Run benchmark
env:
MYSQL_PORT: ${{ job.services.mysql.ports[3306] }}
@@ -312,6 +328,13 @@ jobs:
if [[ ${{matrix.benchmark}} == templated ]]; then
java -jar benchbase.jar -b tpcc -c config/mysql/sample_tpcc_config.xml --create=true --load=true --execute=false --json-histograms results/histograms.json
java -jar benchbase.jar -b ${{matrix.benchmark}} -c config/mysql/sample_${{matrix.benchmark}}_config.xml --create=false --load=false --execute=true --json-histograms results/histograms.json
+ # For anonymization, we load tpcc and anonymize a single table. The workload itself is not executed
+ # FIXME: 'exit 0' is called because there is no benchmark executed and analyzed. Must be removed once the Anonymization script is
+ # fully implemented. See Pull Request 455.
+ elif [[ ${{matrix.benchmark}} == anonymization ]]; then
+ java -jar benchbase.jar -b tpcc -c config/mysql/sample_tpcc_config.xml --create=true --load=true --execute=false --json-histograms results/histograms.json
+ java -jar benchbase.jar -b tpcc -c config/mysql/sample_${{matrix.benchmark}}_config.xml --anonymize=true
+ exit 0
elif [[ ${{matrix.benchmark}} == tpcc-with-reconnects ]]; then
# See Also: WITH_SERVICE_INTERRUPTIONS=true docker/build-run-benchmark-with-docker.sh
java -jar benchbase.jar -b tpcc -c config/mysql/sample_tpcc_config.xml --create=true --load=true
diff --git a/.github/workflows/python.yml b/.github/workflows/python.yml
new file mode 100644
index 000000000..a9e0d2f1e
--- /dev/null
+++ b/.github/workflows/python.yml
@@ -0,0 +1,34 @@
+name: BenchBase (Python)
+
+on:
+ push:
+ branches: [ main ]
+ tags:
+ - 'v*'
+ pull_request:
+ branches: [ main ]
+
+jobs:
+ build:
+ runs-on: ubuntu-latest
+ strategy:
+ matrix:
+ python-version: ["3.10"]
+
+ steps:
+ - uses: actions/checkout@v3
+ - name: Set up Python ${{ matrix.python-version }}
+ uses: actions/setup-python@v4
+ with:
+ python-version: ${{ matrix.python-version }}
+ - name: Install dependencies
+ working-directory: ./scripts/anonymization
+ run: |
+ python -m pip install --upgrade pip
+ pip install -r requirements.txt
+ - name: Check anonymization files with pylint
+ run: |
+ pylint --rcfile=.pylintrc ./scripts/anonymization/src
+ - name: Test anonymization with pytest
+ working-directory: ./scripts/anonymization/src
+ run: pytest test.py
diff --git a/.gitignore b/.gitignore
index 756c1fb4f..d425de6bc 100644
--- a/.gitignore
+++ b/.gitignore
@@ -56,5 +56,8 @@ build/
.*.swp
.env
-
docker-compose-*.tar.gz
+
+# Python
+__pycache__/
+*.py[cod]
\ No newline at end of file
diff --git a/.pylintrc b/.pylintrc
new file mode 100644
index 000000000..c3daa833d
--- /dev/null
+++ b/.pylintrc
@@ -0,0 +1,45 @@
+[MAIN]
+
+# Specify a score threshold under which the program will exit with error.
+fail-under=0.9
+
+[DESIGN]
+
+# Maximum number of arguments for function / method.
+max-args=9
+
+# Maximum number of locals for function / method body.
+max-locals=20
+
+# Maximum number of return / yield for function / method body.
+max-returns=6
+
+# Maximum number of statements in function / method body.
+max-statements=50
+
+# Minimum number of public methods for a class (see R0903).
+min-public-methods=0
+
+
+[FORMAT]
+
+# Maximum number of characters on a single line.
+max-line-length=120
+
+# Maximum number of lines in a module.
+max-module-lines=1000
+
+[REPORTS]
+
+# Python expression which should return a score less than or equal to 10. You
+# have access to the variables 'fatal', 'error', 'warning', 'refactor',
+# 'convention', and 'info' which contain the number of messages in each
+# category, as well as 'statement' which is the total number of statements
+# analyzed. This score is used by the global evaluation report (RP0004).
+evaluation=max(0, 0 if fatal else 10.0 - ((float(5 * error + warning + refactor + convention) / statement) * 10))
+
+# Tells whether to display a full report or only the messages.
+reports=no
+
+# Activate the evaluation score.
+score=yes
diff --git a/config/mysql/sample_anonymization_config.xml b/config/mysql/sample_anonymization_config.xml
new file mode 100644
index 000000000..08843f66a
--- /dev/null
+++ b/config/mysql/sample_anonymization_config.xml
@@ -0,0 +1,42 @@
+
+
+
+
+ MYSQL
+ com.mysql.cj.jdbc.Driver
+ jdbc:mysql://localhost:3306/benchbase?rewriteBatchedStatements=true&allowPublicKeyRetrieval=True&sslMode=DISABLED
+ admin
+ password
+ true
+ TRANSACTION_SERIALIZABLE
+ 128
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/scripts/anonymization/README.md b/scripts/anonymization/README.md
new file mode 100644
index 000000000..57f478889
--- /dev/null
+++ b/scripts/anonymization/README.md
@@ -0,0 +1,352 @@
+# Anonymization
+
+**NOTE:ANONYMIZATION IS A WORK IN PROGRESS AND DOES CURRENTLY NOT ACTUALLY ANONYMIZE THE DATA. THIS FEATURE WILL BE ADDED LATER**
+
+The anonymization module allows applying privacy mechanisms such as differential privacy or column faking to the data.
+The system will pull data from the JDBC connection, anonymize the data and push it back to the DBMS by creating a new table.
+
+## Setup
+
+### Requirements
+
+**Python**: Python 3.10
+
+Requirements can be found inside of the `requirements.txt` file.
+
+Install with pip:
+
+```bash
+pip install -r requirements.txt
+```
+
+### Pylint - Linting
+
+Pylint is automatically added by the requirements and can be run as follows:
+```bash
+pylint --rcfile=.pylintrc src/
+```
+
+### Pytest - Testing
+Pytest is automatically added by the requirements and can be run as follows:
+
+```bash
+pytest ./src/test.py
+```
+
+
+
+## Configuration files (XML)
+
+### Table selection
+
+Multiple tables can be anonymized sequentially by specifying a ``-tag for each of them and defining the table name.
+
+```xml
+
+
+
+
+```
+
+### Differential Privacy anonymization
+
+In order to apply differential privacy, a corresponding ``-tag must be added to each table.
+
+Differential privacy can be configured with the following parameters:
+
+| Name | Default | Possible Value | Description |
+| ----------- | ------- | -------------------------------------------------- | -------------------------------------------------------------------------------------------- |
+| epsilon | 1.0 | Any value > 0 | The privacy budget. Higher values will decrease the privacy guarantee. |
+| pre_epsilon | 0.5 | Any value between 0 and epsilon (epsilon excluded) | The privacy budget spent on preprocessing of the data. Only necessary for continuous columns. |
+| algorithm | mst | One of: `mst,aim,dpctgan,patectgan` | The differential privacy mechanism applied to the data. |
+
+```xml
+
+
+
+```
+
+### Column Information
+
+The columns of a table can be split into four categories:
+
+1. `ignore` - Columns that are ignored by the DP-mechanism. Left untouched.
+2. `categorical` - Columns that contain categorical data.
+3. `continuous` - Columns of data on a continuous domain. Only numerical columns.
+4. `ordinal` - Columns of ordinal meaning. Typically numerical columns with low numers of distinct values.
+
+Each type of column requires its own XML-tag with each member of a type given as a separate tag. (See exampels below for clarification)
+
+If no column type information is given:
+
+- The anonymization process will automatically try to infer the category best suitable for each column.
+- Automatic anonymization can lead to undesired results or failures in the process.
+- To counter this, each column can be defined by hand with the suitable tags.
+
+---
+
+**Ignore the ID-column and anonymize automatically:**
+
+```xml
+
+
+
+```
+
+The ID-column will be removed from the anonymization process and be added back to the data in its original form before pushing back to the DB! This is useful for primary key columns or columns that contain only NULL values.
+
+---
+
+**Define the type of each column individually:**
+
+```xml
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+```
+
+ **Disclaimer**: As soon as the column types are defined by hand, all columns must be defined. It is not possible to only specify some of the categorical columns and let the algorithms do the rest!
+
+### Continuous Columns
+
+The continuous columns will automatically be preprocessed by the algorithm. The lower and upper bounds of the values are inferred in a differentially private way and therefore use some of the preprocessing epsilon budget. Further, values will be binned in order to be applicable to the DP-mechanism. Automatically, the system uses only 10 bins. In order to achieve better data utility, we suggest to manually fine-tune the settings in the config
+
+In the following example, the number of bins is increased to 1000 and the lower and upper bounds are given by hand such that no preprocessing epsilon must be spent!
+
+```xml
+
+
+
+```
+
+The parameters must be added inside of the ``-tag. (See below)
+
+| Name | Default | Possible Value | Description |
+| ----- | ------- | ----------------- | ------------------------------------------- |
+| name | - | Any string | The name of the column. |
+| bins | 10 | Any value | The amount of distinct values in the output.|
+| lower | - | Any value | Lower bound of the values. |
+| upper | - | Any value > lower | Upper bound of the values. |
+
+---
+
+**A full working example could look like this:**
+
+```xml
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+```
+
+## Value faking anonymization
+
+The anonymization module supports value faking to handle sensitive values. The process is decoupled from differential privacy anonymization, allowing for separate or combined anonymization efforts.
+
+**How to handle sensitive values?**
+
+- A ``-tag must be created to signify that column faking should be applied.
+- Column faking can be defined individually on each column with the ``-tag.
+
+The following parameters are available for sensitive values:
+
+| Name | Default | Possible Value | Description |
+| ------- | ------- | ------------------------------------------------ | ---------------------------------------------------------------------------------------------- |
+| name | - | Any string | The name of the column. |
+| method | pystr | Any method provided by the python faker library | The faking method of the library. If the method is not found, a random string will be inserted. |
+| locales | - | A string of supported locales, separated by comma | The locale to produce localized values like chinese street names or english first names. |
+| seed | 0 | Any integer value | The privacy budget spent on preprocessing of the data. Only necessary for continuous columns. |
+
+### Faker categories
+
+Possible methods for faking can be found on the official [Faker documentation](https://faker.readthedocs.io/en/master/)
+
+### Faking example
+
+```xml
+
+
+
+```
+
+## Examples
+
+### Basic
+
+The most basic config will need only the name of the table and the privacy mechanism. All necessary information is collected automatically.
+
+```xml
+
+
+
+```
+
+It is possible to specify multiple tables for the anonymization. Each table will be anonymized on its own
+
+```xml
+
+
+
+
+```
+
+The parameters of differential privacy anonymization can be tuned manually
+
+```xml
+
+
+
+```
+
+### Full config
+
+It is possible to add information about the columns to enable fine-tuning.
+
+```xml
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+```
+
+### Sensitive value handling
+
+Sensitive columns can be anonymized further by replcing the values with fake values. A combination of differential privacy and value faking could look as follows:
+
+```xml
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+```
+
+## Architecture Image
+
+
+
+## More Information
+
+[Differential Privacy Fundamentals](https://www.cis.upenn.edu/~aaroth/Papers/privacybook.pdf)
+
+[Smartnoise Library (Algorithm implementations)](https://github.com/opendp/smartnoise-sdk)
+
+[Python Faker documentation](https://faker.readthedocs.io/en/master/)
diff --git a/scripts/anonymization/architecture.png b/scripts/anonymization/architecture.png
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