This repository contains the source code and data for Cache Shaping, a software-level defense algorithm against cache-based website fingerprinting attacks. Cache Shaping is able to reduce the attack accuracy to a low level by introducing dummy I/O operations with multiple processes.
The dataset and code are for research purposes only. The results of this study are published in the following paper:
Haipeng Li, Nan Niu, Boyang Wang, “Cache Shaping: An Effective Defense Against Cache-Based Website Fingerprinting,” the 12th ACM Conference on Data and Application Security and Privacy (ACM CODASPY 2022), April 24–27, 2022, Baltimore, MD, USA.
The auto_cache_collection directory contains the code to automatically launch cache occupancy attack and collect the cache occupancy information from user's system.
The attack directory contains the code for CNN and LSTM models.
python cnn_cache.py /path/to/your/data /path/to/your/output_model
The open_world directory contains the codes for open-world evaluation.
python ow_test.py /path/to/your/test_data /path/to/your/trained_model
The defense directory contains the code for CacheShaping algorithm
python run_collect.py 'Chrome' /path/to/your/address_lists
The detection directory contains the html and JavaScript files for cache occupancy attack detection.
The utils directory contains the code for preprocessing datasets.
All the original data (i.e., non-defended cache data), defended data and the list of wesites we used both closed-world setting and open-world setting can be found below (last modified: Oct. 2023)
Note: the above links need to be updated every 6 months due to certain settings of OneDrive. If you find the links are expired and you cannot access the data, please feel free to email us (boyang.wang@uc.edu). We will be update the links as soon as we can. Thanks!
We leveraged CNN and LSTM to evaluate the attack and defense performance. Details of the structure and tuned hyperparameters can be found in our paper.
When reporting results that use the dataset or code in this repository, please cite:
Haipeng Li, Nan Niu, Boyang Wang, “Cache Shaping: An Effective Defense Against Cache-Based Website Fingerprinting,” the 12th ACM Conference on Data and Application Security and Privacy (ACM CODASPY 2022), April 24–27, 2022, Baltimore, MD, USA.
Haipeng Li, li2hp@mail.uc.edu, University of Cincinnati
Boyang Wang, boyang.wang@uc.edu, University of Cincinnati