Time Series Anonymization with (k,P)-Anonymity

Requirements

• numpy
• pandas
• loguru
• saxpy
• matplotlib

You can use the requirements.txt file

pip3 install -r requirements.txt

Usage

For a single run:

python3 kp-anonymity.py k_value p_value paa_value /where/is/the/dataset.csv

Parameters

• k_value: Value of k-anonymity (greater than p value)
• p_value: Value of the pattern, p-anonymity
• paa_value: Length of the string that can be used to describe the pattern
• /where/is/the/dataset.csv: Path of the input dataset

For run the tests and produce the histograms of execution time and instant value loss for each run:

python3 runTests.py

You can find the histograms inside "Output" folder as .png files.
The terminal output informs about:

• The parameters that give the lowest "execution time"
• The parameters that give the lowest "instant value loss".

Datasets

In "Dataset" folder there are two datasets that can be use as input dataset. The input datasets are .csv files.

• MLTollsStackOverflow.csv
• NIFTY50-1_day_with_indicators.csv
• Sales_Transaction_Dataset_Weekly_Final.csv

Presentation

Read the presentation: (k,P)-Anonymity

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Work done by:

• Alex Di Stefano
• Christian Stingone