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Countering JPEG anti-forensics based on noise level estimation

Science China(Information Sciences) 2018年第3期61卷 29-42页

作者： Hui ZENG Jingjing YU Xiangui KANG Siwei LYU Guangdong Key Laboratory of Information Security School of Data and Computer ScienceSun Yat-sen University Department of Computer Science University at Albany

Quantization artifact and blocking artifact are the two types of well-known fingerprints of JPEG compression. Most JPEG forensic techniques are focused on these fingerprints. However, recent research shows that these fingerprints can be intentionally concealed via anti-forensics, which in turn makes current JPEG forensic methods vulnerable. A typical JPEG anti-forensic method is adding anti-forensic dither to DCT transform coefficients and erasing blocking artifact to remove the trace of compression history. To deal with this challenge in JPEG forensics, in this paper, we propose a novel countering method based on the noise level estimation to identify the uncompressed images from those forged ones. The experimental results show that the proposed method achieves superior performance on several image databases with only one-dimensional feature. It is also worth emphasizing that the proposed threshold-based method has explicit physical meaning and is simple to be implemented in practice. Moreover, we analyze the strategies available to the investigator and the forger in the case of that they are aware of the existence of each other. Game theory is used to evaluate the ultimate performance when both sides adopt their Nash equilibrium strategies.

关键词： game theory quantization artifact blocking artifact JPEG forensics anti-forensics noise level estimation

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Disguisable Symmetric Encryption Schemes for an anti-forensics Purpose

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China Communications 2010年第6期7卷 56-63页

作者： Ding Ning Gu Dawu Liu Zhiqiang Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai 200240 P. R China

In this paper, we propose a new notion of secure disguisable symmetric encryption schemes, which captures the idea that the attacker can decrypt an encrypted fie to different meaningful values when different keys are put to the decryption algorithm. This notion is aimed for the following anti-forensics purpose： the attacker can cheat the forensics investigator by decrypting an encrypted file to a meaningful file other than that one he encrypted, in the case that he is caught by the forensics investigator and ordered to hand over the key for decryption. We then present a construction of secure disguisable symmetric encryption schemes.

关键词： symmetric encryption obfuscation anti-forensics

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Attacking contrast enhancement forensics in digital images

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Science China(Information Sciences) 2014年第5期57卷 170-182页

作者： CAO Gang ZHAO Yao NI RongRong TIAN HuaWei YU LiFang School of Computer Science Communication University of China Institute of Information Science Beijing Jiaotong University People's Public Security University of China

Currently,plenty of digital image forensic techniques have been proposed and used as diagnostic *** is urgent and significant to assess the reliability of such techniques applied in practical *** this paper,we investigate the security of existing digital image contrast enhancement(CE)forensic *** the standpoint of attackers,we propose two types of attacks,CE trace hiding attack and CE trace forging attack,which could invalidate the forensic detector and fabricate two types of forensic errors,*** CE trace hiding attack is implemented by integrating local random dithering into the design of pixel value *** CE trace forging attack is proposed by modifying the gray level histogram of a target pixel region to counterfeit peak/gap *** trace forging attack is typically applied to create sophisticated composite images which could deceive the prior CE-based composition *** experimental results demonstrate the efficacy of our proposed CE anti-forensic schemes.

关键词： digital forensics anti-forensics attack contrast enhancement composite image histogram

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A Survey of anti-forensic for Face Image Forgery

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Journal of Information Hiding and Privacy Protection 2022年第1期4卷 41-51页

作者： Haitao Zhang aEngineering Research Center of Digital forensics of Ministry of Education School of ComputerNanjing University of Information Science&TechnologyNanjing210044China

Deep learning related technologies,especially generative adversarial network,are widely used in the fields of face image tampering and *** researchers have proposed a variety of passive forensic and related anti-forensic methods for image tampering and forgery,especially face images,but there is still a lack of overview of anti-forensic methods at this ***,this paper will systematically discuss the anti-forensic methods for face image tampering and ***,this paper expounds the relevant background,including the relevant tampering and forgery methods and forensic schemes of face *** former mainly includes four aspects:conventional processing,fake face generation,face editing and face swapping;The latter is mainly the relevant forensic means based on spatial domain and frequency domain using deep learning ***,this paper divides the existing anti-forensic works into three categories according to their method characteristics,namely hiding operation traces,forgery reconstruction and adversarial ***,this paper summarizes the limitations and prospects of the existing anti-forensic technologies.

关键词： anti-forensics face tempering and forgery forensics generative adversarial network

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