Detecting messages of unknown length

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F11%3A00189127" target="_blank" >RIV/68407700:21230/11:00189127 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Detecting messages of unknown length
Original language description
This work focuses on the problem of developing a blind steganalyzer (a steganalyzer relying on machine learning algorithm and steganalytic features) for detecting stego images with different payload. This problem is highly relevant for practical forensicanalysis, since in practice, the knowledge about the steganographic channel is very limited, and the length of hidden message is generally unknown. This paper demonstrates that the discrepancy between payload in training and testing / application imagescan significantly decrease the accuracy of the steganalysis. Two fundamentally different approaches to mitigate this problem are then proposed. The first solution relies on quantitative steganalyzer. The second solution transforms one-sided hypothesis test (unknown message length) to simple hypothesis test by assuming a probability distribution on length of messages, which can be efficiently solved by many machine-learning tools, e.g. by Support Vector Machines. The experimental section
Czech name
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Czech description
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Project
<a href="/en/project/ME10051" target="_blank" >ME10051: AnomalyNET: Anomaly detection enhanced honeypots</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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