"Break Our Steganographic System": The Ins and Outs of Organizing BOSS

This paper summarizes the rst international challenge on steganalysis called BOSS (an acronym for Break Our Steganographic System). We explain the motivations behind the organization of the contest, its rules together with reasons for them, and the steganographic algorithm developed for the contest. Since the image databases created for the contest signi cantly in uenced the development of the contest, they are described in a great detail. Paper also presents detailed analysis of results submitted to the challenge. One of the main di culty of the contest was the discrepancy between training and testing source of images the so-called cover-source mismatch, which forced the participants to design steganalyzers robust w.r.t. a speci c source of images. We also point to other practical issues related to designing steganographic systems and give several suggestions for future contests in steganalysis. 1 BOSS: Break Our Steganographic System During the years 2005 and 2007, the data-hiding community supported by the European Network of Excellence in Cryptology (ECRYPT) launched two watermarking challenges, BOWS [10] and BOWS-2 [1] (abbreviations of Break Our Watermarking System). The purpose of participants of both challenges was to break watermarking systems under di erent scenarios. The purpose of organizers was not only to assess the robustness and the security of di erent watermarking schemes in the environment similar to real application, but to increase the interest in watermarking and to boost the research progress within the eld. Both watermarking contests showed to be popular (BOWS/BOWS2 played more than 300/150 domains and 10/15 participants respectively were ranked), and novel approaches towards breaking watermarking systems were derived during them. This, combined with a thrill associated with organization and participation, inspired us to organize the BOSS (Break Our Steganographic System) challenge. The most important motivation for the contest was to investigate whether content-adaptive steganography improves steganographic security for empirical covers. For the purpose of this contest, a new spatial-domain content-adaptive algorithm called HUGO (Highly Undetectable steGO) was invented [9]. The fact that in adaptive steganography the selection channel (placement of embedding changes) is publicly known, albeit in a probabilistic form, could in theory be exploited by an attacker. Adaptive schemes introduce more embedding changes than non-adaptive schemes because some pixels are almost forbidden from being modi ed, which causes an adaptive scheme to embed with a larger change rate than a non-adaptive one. On the other hand, the changes are driven to hardto-model regions, because the change rate is not an appropriate measure of statistical detectability as it puts the same weight to all pixels. As compared by the state-of-the-art available in mid 2010, HUGO was largely resistant to steganalysis up to 0.4 bits per pixel in 512× 512 grayscale images. The other incentive for organizing the challenge was a hope to encourage the development of new approaches toward steganalysis, pointing to important deadlocks in steganalysis and hopefully nding solutions to them, nding weaknesses of the proposed steganographic system, and nally raising interest in steganalysis and steganography. While running the contest, we became aware of a similar contest organized within the computer vision community [4]. This paper serves as an introduction to a series of papers [removed for review] describing the attacks on HUGO. Here, we describe the contest, image databases, and the HUGO algorithm to give the papers uniform notation and background. 1.1 Requirements and rules In order BOSS challenge to be attractive and fruitful for the community, we have obeyed following conditions and limitations. All participants were ranked by a scalar criterion, the accuracy of detection on a database of 1, 000 512× 512 grayscale images called BOSSRank. Each image in BOSSRank database was chosen to contain secret message of size 104, 857 bits (0.4 bits per pixel) with probability 50% (naturally the list of stego and cover images was secret). To allow all participants to start with the same degree of knowledge about the steganographic system used in the contest, we started the contest with a warm-up phase on June 28, 2010. The very same day the steganographic algorithm HUGO was presented at International Hiding Conference 2010. For the warm-up phase, we also released the source code of the embedding algorithm. To simplify the steganalysis, a training database of 7, 518 512×512 grayscale images (the BOSSBase) was released along with an implementation of the state-of-the-art feature set (the Cross Domain Features (CDF) [7]) for blind steganalysis. Motivation leading us to supply this material, especially the description and implementation of the embedding algorithm, came from the Kerckho s' principle. We wanted all participants to have an easy access to the score of their predictions, yet prevent them to perform an oracle attack on the evaluation 4 A method to reach 100% accuracy by learning the true classi cation of BOSSRank from a very large number of carefully constructed predictions. Camera model # of images # of images in BOSSBase in BOSSRank Leica M9 2267 847 Canon EOS DIGITAL REBEL XSi 1607 0 PENTAX K20D 1398 0 Canon EOS 400D DIGITAL 1354 0 Canon EOS 7D 1354 0 NIKON D7