Reverse JPEG Compatibility Attack
Document type :
Compte-rendu et recension critique d'ouvrage
Title :
Reverse JPEG Compatibility Attack
Author(s) :
Butora, Jan [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Fridrich, Jessica [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Fridrich, Jessica [Auteur]
Journal title :
IEEE Transactions on Information Forensics and Security
Pages :
1444-1454
Publisher :
Institute of Electrical and Electronics Engineers
Publication date :
2019-09-11
ISSN :
1556-6013
English keyword(s) :
Steganography steganalysis JPEG quality factor 100 reverse compatibility rounding errors deep learning
Steganography
steganalysis
JPEG
quality factor 100
reverse compatibility
rounding errors
deep learning
Steganography
steganalysis
JPEG
quality factor 100
reverse compatibility
rounding errors
deep learning
HAL domain(s) :
Informatique [cs]/Traitement du signal et de l'image [eess.SP]
Informatique [cs]/Cryptographie et sécurité [cs.CR]
Informatique [cs]/Cryptographie et sécurité [cs.CR]
English abstract : [en]
A novel steganalysis method for JPEG images is introduced that is universal in the sense that it reliably detects any type of steganography as well as small payloads. It is limited to quality factors 99 and 100. The detection ...
Show more >A novel steganalysis method for JPEG images is introduced that is universal in the sense that it reliably detects any type of steganography as well as small payloads. It is limited to quality factors 99 and 100. The detection statistic is formed from the rounding errors in the spatial domain after decompressing the JPEG image. The attack works whenever, during compression, the discrete cosine transform is applied to integer-valued signal. Reminiscent of the well-established JPEG compatibility steganalysis, we call the new approach the "reverse JPEG compatibility attack." While the attack is introduced and analyzed under simplifying assumptions using reasoning based on statistical signal detection, the best detection in practice is obtained with machine learning tools. Experiments on diverse datasets of both grayscale and color images, five steganographic schemes, and with a variety of JPEG compressors demonstrate the universality and applicability of this steganalysis method in practice.Show less >
Show more >A novel steganalysis method for JPEG images is introduced that is universal in the sense that it reliably detects any type of steganography as well as small payloads. It is limited to quality factors 99 and 100. The detection statistic is formed from the rounding errors in the spatial domain after decompressing the JPEG image. The attack works whenever, during compression, the discrete cosine transform is applied to integer-valued signal. Reminiscent of the well-established JPEG compatibility steganalysis, we call the new approach the "reverse JPEG compatibility attack." While the attack is introduced and analyzed under simplifying assumptions using reasoning based on statistical signal detection, the best detection in practice is obtained with machine learning tools. Experiments on diverse datasets of both grayscale and color images, five steganographic schemes, and with a variety of JPEG compressors demonstrate the universality and applicability of this steganalysis method in practice.Show less >
Language :
Anglais
Popular science :
Non
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