🏔 ALASKA

This repo provides state-of-the-art pre-trained models for steganalysis in the JPEG domain, trained and used to win the ALASKA 1 steganalaysis challenge. Details about the architectures can be found in our paper.

Important Update

A new Alaska competition is now running on Kaggle, note that the settings are very different from the first edition of the competition: Image sizes, Quality factors, Embedding schemes, and Payload.

We have open-sourced our solution in this repo.

Features

• Color seperated feature maps extraction using pretrained SRNet models
• Arbitrary size steganalysis using pretrained detectors
• Notebooks to fine-tune feature extractors and train custom detectors
• Models are shared within the Tensorflow framework, and converted to ONNX for use with other deep learning frameworks.

Please note that shared models are only for JPEG quality factor 95.

Dependecies

Python 3.5+ and dependencies listed in requirements.txt. A Python3 compatible jpeg Package is included in the tools folder. System requirements: Mac OS, Linux (tested on Ubuntu 18.04)

Getting started - Downloading models

Please run the following python code to download the available models.

import requests
import zipfile
import os
home = os.path.expanduser("~")
user = home.split('/')[-1]

url = 'http://dde.binghamton.edu/download/alaska/models.zip'
local = home + '/alaska/models.zip'

r = requests.get(url)
with open(local, 'wb') as f:
    for chunk in tqdm(r.iter_content(chunk_size=2**10)): 
        if chunk:
            f.write(chunk)
with zipfile.ZipFile(local, 'r') as zipref:
    zipref.extractall(home + '/alaska/')
    
os.remove(local)

Getting started - Downloading datasets

This repo comes with minimal image examples, the complete datasets used to train these models have been removed from the official Alaska website by the organizers.

References

Please consider citing our paper if you find this repository useful.

@inproceedings{Yousfi2019Alaska,
 author = {Yousfi, Yassine and Butora, Jan and Fridrich, Jessica and Giboulot, Quentin},
 title = {Breaking ALASKA: Color Separation for Steganalysis in JPEG Domain},
 booktitle = {Proceedings of the ACM Workshop on Information Hiding and Multimedia Security},
 series = {IH\&\#38;MMSec'19},
 year = {2019},
 isbn = {978-1-4503-6821-6},
 location = {Paris, France},
 pages = {138--149},
 numpages = {12},
 url = {http://doi.acm.org/10.1145/3335203.3335727},
 doi = {10.1145/3335203.3335727},
 acmid = {3335727},
 publisher = {ACM},
 address = {New York, NY, USA},
}