- This is a customed-implementation version of NetCLR [1] framework to check the performance of augmented network traces in realistc website fingerprinting w/ own manipulation rules. The original code is splitted into several python files for convenience.
- If you implement this code, specify the path of
DATA_ABSOLUTE_PATH
andLOG_ABSOLUTE_PATH
in main.py. (* Also you can add other rules inAugmentor
ataugmentor.py
) - This code is re-implemented that fits to 'sizes' and 'timestamps' features unlike the original code, 'bursts'.
python main.py --o "models/nj_4_e_" --logs_name "nj_4_e_100.txt" -b 256 -n 100 -t 0.5 --method 0
\---src
| augmentor.py
| backbone.py
| common.py
| main.py
| netclr.py
| usage.py
|
+---finetuning
| | backbone.py
| | cw_train.py
| | graphing.py
| | main.py
| | single.py
| |
| +---log
| +---results
|
+---logs
+---models
+---others
| \---cfg2
| main2.py
[1] Alireza Bahramali, Ardavan Bozorgi, and Amir Houmansadr. 2023. Realistic Website Fingerprinting By Augmenting Network Traces. In Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security (CCS ’23), November 26–30, 2023, Copenhagen, Denmark. ACM, New York, NY, USA, 15 pages. https://doi.org/10.1145/3576915.3616639
@inproceedings{3576915.3616639,
author = {Bahramali, Alireza and Bozorgi, Ardavan, and Houmansadr, Amir},
title = {Realistic Website Fingerprinting By Augmenting Network Traces},
booktitle = {Proceedings of
the 2023 ACM SIGSAC Conference on Computer and Communications Security},
series = {CCS '23},
year = {2023},
location = {Copenhagen, Denmark},
numpages = {15},
url = {https://doi.org/10.1145/3576915.3616639},
doi = {10.1145/3576915.3616639},
publisher = {ACM},
address = {New York, NY, USA},
}