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AdVeil Prototype

Dependencies

Getting everything to run (tested on Ubuntu 20.04.2 LTS)

0) Install dependencies (Ubuntu): 0) Install dependencies (CentOS):
sudo apt-get install build-essential sudo yum groupinstall 'Development Tools'
sudo apt-get install cmake sudo yum install cmake
sudo apt-get install libgmp3-dev sudo yum install gmp-devel
sudo apt-get install golang-go sudo yum install golang
  1. Globally install Microsoft SEAL 3.2.0:
wget https://github.com/microsoft/SEAL/archive/refs/tags/v3.2.0.tar.gz
tar -xvf v3.2.0.tar.gz
cd SEAL-3.2.0/native/src
cmake .
make
sudo make install
  1. Compile the SealPIR library in adveil/C/:
cd C/
cmake .
make -j
  1. Run the desired experiment! (See next section)

Running experiments

  1. On the Broker machine:
bash run_targeting.sh
    --port 8000 \
    --numprocs 1
  1. On the client machine:
bash run_client.sh --brokerhost localhost --brokerport 8000 --trials 10 --autoclose

or cycle through all experiments at once:

bash clicycle.sh --brokerhost localhost --brokerport 8000 --trials 10 --autoclose

The client triggers the start of the experiment on the server. The targeting_params.sh script iterates through a parameters and initializes the server with the params. Each client run starts a new experiment under the specified parameters and saves it to a JSON file. Therefore, to cycle through all experiments, we re-run the client many times (e.g., 100); this is done automatically using clicycle.sh. Resulting experiment summary will be saved in the adveil/results directory.

Converting the generated files

All results as saved as .json files (one per experiment) in the adveil/results`` directory. Use concat.pyto merge multiple files into one.json``` array file.

python concat.py --dir ../results --out ../results/targeting.json

Issues with running on MacOS

While the code has been tested on MacOS (Big Sur), there is a bug in the cgo interface. On Linux, uint64_t is cast as C.ulong in the Go code which does not work on Mac (seems to be a bug?) The compiler will handle switching between two instances of sealpir.go to work around this issue.

Evaluating accuracy of the targeting data structure

Please see AdVeil Accuracy for instructions on reproducing the ANN accuracy experiments.

Acknowledgements

Important Warning

This implementation of AdVeil is intended as a proof-of-concept prototype only! The code was implemented for research purposes and has not been vetted by security experts. As such, no portion of the code should be used in any real-world or production setting!

License

Copyright © 2021-2023 Sacha Servan-Schreiber

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

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Prototype implementation of a privacy-preserving targeted advertising ecosystem.

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