Results 21 to 30 of about 3,467 (203)
Deep learning for steganalysis: evaluating model robustness against image transformations. [PDF]
Front Artif IntellAlrusaini OA.
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From Blind to Quantitative Steganalysis [PDF]
IEEE Transactions on Information Forensics and Security, 2009 A quantitative steganalyzer is an estimator of the number of embedding changes introduced by a specific embedding operation. Since for most algorithms the number of embedding changes correlates with the message length, quantitative steganalyzers are important forensic tools.
Pevný, T, Fridrich, J, Ker, A
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Locating secret messages based on quantitative steganalysis
Mathematical Biosciences and Engineering, 2019 Steganography poses a serious challenge to forensics because investigators cannot identify even traces of secret messages embedded using a steganographer.
Chunfang Yang +4 more
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Adversarial subdomain adaptation network for mismatched steganalysis
网络与信息安全学报, 2022 Once data in the training and test sets come from different cover sources, that is, under the condition of cover source mismatch, it usually makes the detection accuracy rate of an outstanding steganalysis model to be reduced.In practical applications ...
Lei ZHANG, Hongxia WANG
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Quantized Gaussian JPEG Steganography and Pool Steganalysis
IEEE Access, 2022 Currently, algorithms for compressed image steganography mainly embed hidden message by minimizing the resulting distortion or statistical detectability.
Mohammed Aloraini +2 more
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Steganalysis Bukti Digital pada Media Storage Menggunakan Metode GCFIM
JISKA (Jurnal Informatika Sunan Kalijaga), 2020 Steganography is an anti-forensic technique that allows a criminal to hide information in other messages, so that during an examination it will be difficult to obtain evidence of the crime information.
Muh Hajar Akbar +2 more
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Steganalysis of Adaptive Multi-Rate Speech Using Statistical Characteristics of Pitch Delay [PDF]
Journal of Universal Computer Science, 2019 Steganography is a promising technique for covert communications. However, illegal United States of Americage of this technique would facilitate cybercrime activities and thereby pose a great threat to information security.
Hui Tian +5 more
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Sensitivity of deep learning applied to spatial image steganalysis [PDF]
PeerJ Computer Science, 2021 In recent years, the traditional approach to spatial image steganalysis has shifted to deep learning (DL) techniques, which have improved the detection accuracy while combining feature extraction and classification in a single model, usually a ...
Reinel Tabares-Soto +8 more
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About JPEG Images Parameters Impact to Steganalys Accuracy
Кібернетика та комп'ютерні технології, 2021 Introduction. Existing examples of illegal use of computer steganography prove the need for the development of stegananalytical methods and systems as one of the most important areas of cybersecurity.
N. Koshkina
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Steganalysis Using Wavelet Transform
Journal of Kufa for Mathematics and Computer, 2012 Techniques and applications for information hiding have become increasingly more sophisticated and widespread. With high-resolution digital images as carriers, detecting the presence of hidden messages has also become considerably more difficult. It is sometimes possible, nevertheless, to detect (but not necessarily decipher) the presence of embedded ...
Waleed . A Mahmud +2 more
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