Stego key recovery method for F5 steganography with matrix encoding

Liu, Jiufen; Yang, Ching-Nung; Wang, Junchao; Shi, Yanan

doi:10.1186/s13640-020-00526-2

Cited by 7 publications

(5 citation statements)

References 39 publications

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“…F5 reduces the propagation of steganographic information through the carrier. The method described in [32] aims to get the check matrix and shuffling key of F5 steganography by guessing the embedding ratios and telling the difference between real and fake keys by looking at the bit sequence distributions. Notably, it may encounter challenges in accurately recovering keys at particularly high or low embedding ratios.…”

Section: Related Work On Image Steganographymentioning

confidence: 99%

Enhancing Steganography through Optimized Quantization Tables

Brūzgienė,

Venčkauskas,

Grigaliūnas

et al. 2024

Electronics

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This paper addresses the scientific problem of enhancing the security and capacity of steganographic methods for protecting digital media. The primary aim is to develop an advanced steganographic technique that optimizes quantization tables to surpass the traditional F5 algorithm in terms of security, capacity, and robustness. The novelty of this research lies in the introduction of the F5A method, which utilizes optimized quantization tables to significantly increase the capacity for concealed information while ensuring high-quality image retention and resistance to unauthorized content recovery. The F5A method integrates cryptographic keys and features to detect and prevent copyright infringement in real time. Experimental evaluations demonstrate that the F5A method improves the mean square error and peak signal-to-noise ratio indices by 1.716 and 1.121 times, respectively, compared to the traditional F5 algorithm. Additionally, it increases the steganographic capacity by up to 1.693 times for smaller images and 1.539 times for larger images. These results underscore the effectiveness of the F5A method in enhancing digital media security and copyright protection.

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Section: Related Work On Image Steganographymentioning

confidence: 99%

Enhancing Steganography through Optimized Quantization Tables

Brūzgienė,

Venčkauskas,

Grigaliūnas

et al. 2024

Electronics

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“…Finally, the hypothesis testing theory was adopted to confirm the correctness of the embedding positions. Inspired by the work of Liu et al [44], series of steganalysis methods are proposed to recover the stego key towards LSBR, LSBM [38], F5 [41], and OutGuess [45]. Recently, towards adaptive steganography, [46] proposed a solution.…”

Section: Related Workmentioning

confidence: 99%

“…To our knowledge, most of steganographic algorithms focus on the first and second layer while ignoring the latter two layers of studies [33][34][35][36][37][38][39][40][41]. In practice, the ultimate goal of steganalysis is to reconstruct the hidden bits, namely, forensic steganalysis [42].…”

Section: Introductionmentioning

confidence: 99%

Novel Hidden Bit Location Method towards JPEG Steganography

Pan

Qiao

et al. 2022

Security and Communication Networks

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Image steganalysis has been widely studied, most of which can only complete the binary task of identifying the existence of hidden bits in an inquiry image. Currently, although some algorithms have been proposed to locate hidden bits, most of them mainly focus on the spatial domain, while usually ignoring the study of locating secret bits hidden in DCT domain for JPEG image. To address that challengeable problem, in this paper, towards two classical steganographic algorithms JSteg and F5, hiding bits in DCT domain, we propose a novel payload location method. The principal step of payload location is to estimate the cover image. We novelly propose to assign the different weights to the DCT coefficient residual in virtue of the texture of regions measured by the local variance, leading to the remarkable improvement of location results. Compared with the state of the art, the numerical experiments empirically verify that our proposed location method achieves the superior performance. In particular, when locating hidden bits in JSteg steganographic images with quality factor of 95 at the payload 0.1, the accuracy of location is remarkably improved from 46.18% to 90.22%.

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“…All factors are considered, such as secret message length or JPEG quality factors. Also, authors in [70] claim that there are no effective methods to recover the steganography key because it is difficult to statistically distinguish the coefficient sequences selected by true and false keys. Therefore, the author's paper proposes a method for recovering the steganography key of a JPEG image steganography.…”

Section: Breaking the Transform Domain Techniquesmentioning

confidence: 99%

Advanced Methods of Detection of the Steganography Content

Hendrych

Ličev

2019

Lecture Notes in Electrical Engineering

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Steganografie může být využita k nelegálním aktivitám. Proto je velmi důležité být připraven. K detekci steganografického obrázku máme k dispozici techniku známou jako stegoanalýza. Existují různé typy stegoanalýzy v závislosti na tom, zda je znám originální nosič nebo zdali víme, jaký byl použit algoritmus pro vložení tajné zprávy. Z hlediska praktického použití jsou nejdůležitější metody "slepé stagoanalýzy", které zle aplikovat na obrazové soubory a jelikož nemáme originální nosič pro srovnání. Tato doktorská práce popisuje metodologii obrazové stegoanalýzy. V této práci je důležité porozumět chování cíleného steganografického algoritmu. Pak můžeme využít jeho slabiny ke zvýšení detekční schopnosti a úspěšnosti kategorizace. Primárně se zaměřujeme na prolomení steganografického algoritmu OutGuess2.0 a sekundárně na algoritmus F5. Analyzujeme schopnost detektoru, který využívá proces kalibrace, výpočtu shlukování a mělkou neuronovou síť k detekci přítomnosti steganografické zprávy na podezřelém snímku. Nový přístup a výsledky jsou sepsány v této doktorské práci. Hlavní přínosy disertační práce jsou následující: 1. Detekce stegogramů vytvořených steganografickými algoritmy OutGuess2.0 a F5. 2. Vysoká úspěšnost klasifikace -s ohledem na sensitivitu testu. 3. Invariance sensitivity testu vůči velikosti tajné zprávy. 4. Podpora různých rozlišení a barevné hloubky obrázků. 5. Aplikace mělké neuronové sítě. 6. Aplikace filtrování makrobloků JPEG obrázků pro zvýšení úspěšnosti klasifikace. 7. Publikování výzkumu -všechny prezentované přínosy jsou publikovány na mezinárodní konferenci nebo v časopise.

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Stego key recovery method for F5 steganography with matrix encoding

Cited by 7 publications

References 39 publications

Enhancing Steganography through Optimized Quantization Tables

Enhancing Steganography through Optimized Quantization Tables

Novel Hidden Bit Location Method towards JPEG Steganography

Advanced Methods of Detection of the Steganography Content

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