Transportation-theoretic image counterforensics to First Significant Digit histogram forensics

Pasquini, Cecilia; Comesana-Alfaro, Pedro; Pérez-González, Fernando; Boato, Giulia

doi:10.1109/icassp.2014.6854090

Cited by 21 publications

(19 citation statements)

References 11 publications

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“…Positive reports about FSD-based compression forensics in the literature have also led to a number of counter-forensic techniques [27] that attempt to restore block-DCT coefficient FSD histograms after JPEG compression [28,29]. Yet we demonstrated in a recent work [20] that restoration algorithms under a minimum cost constraint can lead to detectable artifacts in the histograms of second significant digits.…”

Section: Experiments With Block-dct Ssdsmentioning

confidence: 92%

Compression Forensics Beyond The First Significant Digit

Chakraborty¹,

Kirchner²

2016

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We study characteristics of the second significant digits of block-DCT coefficients computed from digital images. Following previous works on compression forensics based on first significant digits, we examine the merits of stepping towards significant digits beyond the first. Our empirical findings indicate that certain block-DCT modes follow Benford's law of second significant digits extremely well, which allows us to distinguish between never-compressed images and decompressed JPEG images even for the highest JPEG compression quality of 100. As for multiple-compression forensics we report that second significant digit histograms are highly informative on their own, yet cannot further improve already good performances of classification schemes that work with first significant digits alone.

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Section: Experiments With Block-dct Ssdsmentioning

confidence: 92%

Compression Forensics Beyond The First Significant Digit

Chakraborty¹,

Kirchner²

2016

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“…Soon afterwards a second algorithm was proposed in [3], which did not perfectly enforce the target distribution either. This issue was solved in [4], but the distortion minimisation algorithm therein was heuristic. Finally, a completely general solution to the problem of optimum first-order counterforensics appeared in [5], and its authors showcased their approach by applying it to the problem of optimum FSD counterforensics.…”

Section: Introductionmentioning

confidence: 99%

Towards Optimum Counterforensics of Multiple Significant Digits Using Majorisation-Minimisation

Balado

Silvestre

2018

2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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“…When the analysis is limited to first order statistics and the attack must satisfy a per-pixel distortion constraint, the optimum attack is known and the MPA corresponds to this attack (see [8] and [7] for attacks in the spatial and frequency domain respectively). The optimum attack in the DCT domain has been used in [10] to build an adversary-aware SVM, which was shown to be able to resist to other double JPEG counter-forensic attacks belonging to the same class, namely, first order attacks (e.g., the attack to the FSD coefficients [4], [5]). …”

Section: Mpa-aware Svm Detectormentioning

confidence: 99%

“…In turn, a number of powerful attacks which are capable to prevent a correct detection while keeping the mean squared error distortion introduced by the attack limited, have been developed. In [4] and [5], counterforensic schemes were introduced to remove the artefacts of double compression in the distribution of the first significant digits (FSD) of the DCT coefficients thus making the detector fail [6]. In [7], a universal double JPEG attack against first order based detectors has been proposed, which extends to the DCT domain the universal attack in the pixel domain originally proposed in [8].…”

Section: Introductionmentioning

confidence: 99%

Higher-order, adversary-aware, double JPEG-detection via selected training on attacked samples

Bami

Nowroozi

Tondi

2017

2017 25th European Signal Processing Conference (EUSIPCO)

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Abstract-In this paper we present an adversary-aware double JPEG detector which is capable of detecting the presence of two JPEG compression steps even in the presence of heterogeneous processing and counter-forensic (C-F) attacks. The detector is based on an SVM classifier fed with a large number of features and trained to recognise the traces left by double JPEG detection in the presence of attacks. Since it is not possible to train the SVM on all possible kinds of processing and C-F attacks, a selected set of images, manipulated with a limited number of attacks is added to the training set. The processing tools used for training are chosen among those that proved to be most effective in disabling double JPEG detection. Experimental results prove that training on such a kind of most powerful attacks allows good detection in the presence of a much wider variety of attacks and processing. Good performance are retained over a wide range of compression quality factors.

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Transportation-theoretic image counterforensics to First Significant Digit histogram forensics

Cited by 21 publications

References 11 publications

Compression Forensics Beyond The First Significant Digit

Compression Forensics Beyond The First Significant Digit

Towards Optimum Counterforensics of Multiple Significant Digits Using Majorisation-Minimisation

Higher-order, adversary-aware, double JPEG-detection via selected training on attacked samples

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