A review of digital image forensics

Abstract The manipulation of digital images has become very common in recent years. Thus, it is possible to cut, clone, and resize an image very quickly, which makes it challenging to validate the integrity and authenticity of images. Furthermore, digital images can be used by forensic experts in their forensic investigations. In this context, digital image forensics (DIF) has emerged as an essential area of expertise focused on verifying the authenticity and integrity of digital files. This paper presents a literature review of DIF, covering active and passive methods as well as those based on deep learning, and our work presents a vast and updated set of references synthesized in textual, tabular, and graphic form.

[1]  Jiwu Huang,et al.  Large-Scale JPEG Image Steganalysis Using Hybrid Deep-Learning Framework , 2016, IEEE Transactions on Information Forensics and Security.

[2]  Gorthi R. K. Sai Subrahmanyam,et al.  Exploring the learning capabilities of convolutional neural networks for robust image watermarking , 2017, Comput. Secur..

[3]  Jiantao Zhou,et al.  Fast and Effective Image Copy-Move Forgery Detection via Hierarchical Feature Point Matching , 2019, IEEE Transactions on Information Forensics and Security.

[4]  Francisco Madeiro,et al.  Word-Hunt: A LSB Steganography Method with Low Expected Number of Modifications per Pixel , 2016, IEEE Latin America Transactions.

[5]  Muhammad Haroon Yousaf,et al.  A generic passive image forgery detection scheme using local binary pattern with rich models , 2017, Comput. Electr. Eng..

[6]  Bin Li,et al.  Large-scale JPEG steganalysis using hybrid deep-learning framework , 2016, ArXiv.

[7]  Xiaofeng Wang,et al.  Source camera identification from image texture features , 2016, Neurocomputing.

[8]  Fernando Pérez-González,et al.  A Random Matrix Approach to the Forensic Analysis of Upscaled Images , 2017, IEEE Transactions on Information Forensics and Security.

[9]  M. Shobana,et al.  EFFICIENT METHOD FOR HIDING DATA BY PIXEL INTENSITY , 2013 .

[10]  Zahid Mehmood,et al.  A robust technique for copy-move forgery detection and localization in digital images via stationary wavelet and discrete cosine transform , 2018, J. Vis. Commun. Image Represent..

[11]  Ayman Ibaida,et al.  Wavelet-Based ECG Steganography for Protecting Patient Confidential Information in Point-of-Care Systems , 2013, IEEE Transactions on Biomedical Engineering.

[12]  Nasir Memon,et al.  PRNU-Based Camera Attribution From Multiple Seam-Carved Images , 2017, IEEE Transactions on Information Forensics and Security.

[13]  Yizhi Liu,et al.  Copy-move forgery detection based on deep learning , 2017, 2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI).

[14]  Dong-Ming Yan,et al.  Distinguishing Between Natural and Computer-Generated Images Using Convolutional Neural Networks , 2018, IEEE Transactions on Information Forensics and Security.

[15]  Taha H. Rassem,et al.  Block-based discrete wavelet transform-singular value decomposition image watermarking scheme using human visual system characteristics , 2016, IET Image Process..

[16]  Ming Xu,et al.  Robust Multi-Classifier for Camera Model Identification Based on Convolution Neural Network , 2018, IEEE Access.

[17]  Ferda Ernawan,et al.  A Robust Image Watermarking Technique With an Optimal DCT-Psychovisual Threshold , 2018, IEEE Access.

[18]  Rosziati Ibrahim,et al.  A New Digital Watermarking Algorithm Using Combination of Least Significant Bit (LSB) and Inverse Bit , 2011, ArXiv.

[19]  Ahmed Al-Ani,et al.  A steganography embedding method based on edge identification and XOR coding , 2016, Expert Syst. Appl..

[20]  K. S. Bapat Comparative Analysis of Watermarking in Digital Images Using DCT & DWT , 2013 .

[21]  Jiangqun Ni,et al.  Efficient JPEG Steganography Using Domain Transformation of Embedding Entropy , 2018, IEEE Signal Processing Letters.

[22]  Nabin Ghoshal,et al.  A steganographic scheme for colour image authentication (SSCIA) , 2011, 2011 International Conference on Recent Trends in Information Technology (ICRTIT).

[23]  S. Edward Jero,et al.  Curvelets-based ECG steganography for data security , 2016 .

[24]  Shih-Fu Chang,et al.  Camera Response Functions for Image Forensics: An Automatic Algorithm for Splicing Detection , 2010, IEEE Transactions on Information Forensics and Security.

[25]  Shamim Ahmed Laskar,et al.  STEGANOGRAPHY BASED ON RANDOM PIXEL SELECTION FOR EFFICIENT DATA HIDING , 2013 .

[26]  Matthieu Urvoy,et al.  Perceptual DFT Watermarking With Improved Detection and Robustness to Geometrical Distortions , 2014, IEEE Transactions on Information Forensics and Security.

[27]  Xiangui Kang,et al.  Revealing Traces of Image Resampling and Resampling Antiforensics , 2017, Adv. Multim..

[28]  Anirban Bose,et al.  Spread Spectrum Watermark Detection on Degraded Compressed Sensing , 2017, IEEE Sensors Letters.

[29]  Reza Safabakhsh,et al.  A new steganography method which preserves histogram: Generalization of LSB++ , 2014, Inf. Sci..