In order not to provide some elements regarding the ALASKA#2 challange ahead in advance, the present website only proposed offers two main types of materials.
- First, and perhaps most important ones, we provide datasets. The main dataset is made of a set of 80,000 raw images ; the images are numbered by Digital still camera model as described in this simple text file.
Besides, for easy use by the community we also provide also several processed dataset:
Uncompressed color and grayscale image datasets (of size 512x512, 256x256 for easy use in Deep learning and various sizes).
JPEG compressed images datasets (with quality factors: 100 , 95 , 90 , 85 , 80 , 75 and various QF).
- Second we also provide the scripts that have been used to convert the raw images into jpeg format. Those python scripts use the main following library: numpy (version 1.14.5), pillow the Python Imaging Library (version 5.2), and the open-source raw image processing program Rawtherapee(version 5.7).
Those scripts are those that we have used to generate the various datasets from the raw image files.
- For any question, regarding either image datasets and/or conversion scripts, contact us at email@example.com.
- While all the materials are available under the Creative Commons BY-NC-ND license for use in any research works we kindly ask you to credit our (enormous) work by either refering to the alaska website URL or, more relevant, by simply citing one of the associated papers:
The ALASKA Steganalysis Challenge: A First Step Towards Steganalysis "into the wild", Published in the 7th ACM IH&MMSec conference.
The contest will take place over spring 2020 lasting about 3 months in total (more details to come). The rules are the following :
- Submission can be made only throughout the Kaggle Competitions website.
- Cash prices of at least $5000 will be provided for the best three users.
Those winners will be asked to provide the source code of their detectors to get their price.
We strongly encourage the five top-scoring teams to propose a paper to WIFS 2020 ; a $3000 travel grant will be offered for accepted papers.
- Competitors cannot submit more than one trial every four hours.
Each submission is evaluated over a randomly selected subset of 80% of the testing set. The final results, when contest closes, will be adjusted with evaluation over the whole testing set.
The ranking is made using the empirical probability of missed detection for a fixed empirical probability of false alarm of 5%. We will count of many images with hidden data are incorrectly classified as covers when exactly 5% of cover images are incorrectly classified as containing hidden data.
- Anyone can download the dataset from present website.
The present website will also allow users to submit their proposal once the official challenge will be over (to avoid providing side informations) ; for this users must create an account.
Those accounts will only be used for statistical purposes and communications will be made only regarding the ALASKA challenge.
As indicated in the Material section you are free to download and use for any non-commercial purposes all datasets that are made available on this website. This especially includes the raw and processed images dataset as well as all conversion scripts in order to create any custom dataset that fits your need. We however kindly ask you to credit our (enormous work) by either referng to the alaska website or, more relevant, to simply cite one of the associated paper :
- The ALASKA Steganalysis Challenge: A First Step Towards Steganalysis ``into the wild''., Published in the 7th ACM IH&MMSec conference.
The ALASKA contest has been, in part, inspired by the BOSS competition and has been jointly and proudly organized by:
We would like to thank all the individuals that help us organizing this contest. Those are mainly (but not exclusively):
- Antoine Prudhomme, for creating the present website.
- Julien Flamant, Jean-Baptiste Gobin, Bertrand De La Morlais, Florent Pergoud, Luc Rodrigues, Pascal Royer and Emile Touron for kindly provide some of their raw images as well as Dirk Borghys for the joint work on assessment of impact of raw images development on steganalysis performance (that gives birth to ALASKA dataset and challenge).
- The computer resources department of Troyes University of Technology who helped us with all their advices and suggestions.