59,912 research outputs found
Phylogenetic information complexity: Is testing a tree easier than finding it?
Phylogenetic trees describe the evolutionary history of a group of
present-day species from a common ancestor. These trees are typically
reconstructed from aligned DNA sequence data. In this paper we analytically
address the following question: is the amount of sequence data required to
accurately reconstruct a tree significantly more than the amount required to
test whether or not a candidate tree was the `true' tree? By `significantly',
we mean that the two quantities behave the same way as a function of the number
of species being considered. We prove that, for a certain type of model, the
amount of information required is not significantly different; while for
another type of model, the information required to test a tree is independent
of the number of leaves, while that required to reconstruct it grows with this
number. Our results combine probabilistic and combinatorial arguments.Comment: 15 pages, 3 figure
Universal Image Steganalytic Method
In the paper we introduce a new universal steganalytic method in JPEG file format that is detecting well-known and also newly developed steganographic methods. The steganalytic model is trained by MHF-DZ steganographic algorithm previously designed by the same authors. The calibration technique with the Feature Based Steganalysis (FBS) was employed in order to identify statistical changes caused by embedding a secret data into original image. The steganalyzer concept utilizes Support Vector Machine (SVM) classification for training a model that is later used by the same steganalyzer in order to identify between a clean (cover) and steganographic image. The aim of the paper was to analyze the variety in accuracy of detection results (ACR) while detecting testing steganographic algorithms as F5, Outguess, Model Based Steganography without deblocking, JP Hide&Seek which represent the generally used steganographic tools. The comparison of four feature vectors with different lengths FBS (22), FBS (66) FBS(274) and FBS(285) shows promising results of proposed universal steganalytic method comparing to binary methods
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