Rich Models for Steganalysis of Digital Images

LIBSVM: A library for support vector machines

Chang, C.-C., & Lin, C.-J. (2011) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/1961189.1961199 · Cited by 40,918 · see citing works

Bagging predictors

Breiman, L. (1996) · Machine Learning · doi:10.1007/bf00058655 · Cited by 16,325 · see citing works

Libsvm : A library for support vector machines

Ferrari, V. (2008) · Medical Entomology and Zoology · Cited by 10,124 · see citing works

Information Hiding Techniques for Steganography and Digital Watermarking

Katzenbeisser, S., & Petitcolas, F. A. P. (1999) · Cited by 1,895 · see citing works

Optimization by Direct Search: New Perspectives on Some Classical and Modern Methods

Kolda, T. G., Lewis, R. M., & Torczon, V. J. (2003) · SIAM Review · doi:10.1137/s003614450242889 · Cited by 1,659 · see citing works

Feature extraction : foundations and applications

Guyon, I., Gunn, S. R., Nikravesh, M., & zadeh, L. N. (2006) · Cited by 1,658 · see citing works

Ensemble Classifiers for Steganalysis of Digital Media

Kodovský, J., Fridrich, J., & Holub, V. (2011) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2011.2175919 · Cited by 1,072 · see citing works

Using High-Dimensional Image Models to Perform Highly Undetectable Steganography

Pevný, T., Filler, T., & Bas, P. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-16435-4_13 · Cited by 1,026 · see citing works

Minimizing Additive Distortion in Steganography Using Syndrome-Trellis Codes

Filler, T., Judas, J., & Fridrich, J. (2011) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2011.2134094 · Cited by 968 · see citing works

Steganalysis by Subtractive Pixel Adjacency Matrix

Pevný, T., Bas, P., & Fridrich, J. (2010) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2010.2045842 · Cited by 899 · see citing works

Steganalysis by subtractive pixel adjacency matrix

Pevný, T., Bas, P., & Fridrich, J. (2009) · ACM workshop on Multimedia and security · doi:10.1145/1597817.1597831 · Cited by 771 · see citing works

Edge Adaptive Image Steganography Based on LSB Matching Revisited

Luo, W., Huang, F., & Huang, J. (2010) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2010.2041812 · Cited by 661 · see citing works

Steganography in Digital Media

Fridrich, J. (2009) · Cambridge University Press eBooks · doi:10.1017/cbo9781139192903 · Cited by 568 · see citing works

Steganalysis using image quality metrics

Avcıbaş, İ., Memon, N. D., & Sankur, B. (2003) · IEEE Transactions on Image Processing · doi:10.1109/tip.2002.807363 · Cited by 563 · see citing works

Steganography in digital media: principles, algorithms, and applications

(2010) · Choice Reviews Online · doi:10.5860/choice.47-6907 · Cited by 546 · see citing works

Feature-Based Steganalysis for JPEG Images and Its Implications for Future Design of Steganographic Schemes

Fridrich, J. (2004) · Lecture notes in computer science · doi:10.1007/978-3-540-30114-1_6 · Cited by 465 · see citing works

Detecting Hidden Messages Using Higher-Order Statistics and Support Vector Machines

Lyu, S., & Farid, H. (2002) · Lecture notes in computer science · doi:10.1007/3-540-36415-3_22 · Cited by 456 · see citing works

Steganalysis of additive-noise modelable information hiding

Harmsen, J., & Pearlman, W. A. (2003) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.476813 · Cited by 400 · see citing works

A Markov Process Based Approach to Effective Attacking JPEG Steganography

Shi, Y. Q., Chen, C., & Chen, W. (2007) · Lecture notes in computer science · doi:10.1007/978-3-540-74124-4_17 · Cited by 346 · see citing works

Gibbs Construction in Steganography

Filler, T., & Fridrich, J. (2010) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2010.2077629 · Cited by 302 · see citing works

New blind steganalysis and its implications

Goljan, M., Fridrich, J., & Holotyak, T. (2006) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.643254 · Cited by 267 · see citing works

JPEG image steganalysis utilizing both intrablock and interblock correlations

Chen, C., & Shi, Y. Q. (2008) · IEEE International Symposium on Circuits and Systems proceedings · doi:10.1109/iscas.2008.4542096 · Cited by 244 · see citing works

Image Steganalysis with Binary Similarity Measures

Avcıbaş, İ., Kharrazi, M., Memon, N. D., & Sankur, B. (2005) · EURASIP Journal on Advances in Signal Processing · doi:10.1155/asp.2005.2749 · Cited by 190 · see citing works

Revisiting weighted stego-image steganalysis

Ker, A. D., & Böhme, R. (2008) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.766820 · Cited by 181 · see citing works

Steganalysis in high dimensions: fusing classifiers built on random subspaces

Kodovský, J., & Fridrich, J. (2011) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.872279 · Cited by 128 · see citing works

A machine learning based scheme for double JPEG compression detection

Chen, C., Shi, Y. Q., & Su, W. (2008) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr.2008.4761645 · Cited by 117 · see citing works

Steganalysis of Content-Adaptive Steganography in Spatial Domain

Fridrich, J., Kodovský, J., Holub, V., & Goljan, M. (2011) · Lecture notes in computer science · doi:10.1007/978-3-642-24178-9_8 · Cited by 102 · see citing works

Design of adaptive steganographic schemes for digital images

Filler, T., & Fridrich, J. (2011) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.872192 · Cited by 97 · see citing works

Modern steganalysis can detect YASS

Kodovský, J., Pevný, T., & Fridrich, J. (2010) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.838768 · Cited by 89 · see citing works

Steganalysis based on Markov Model of Thresholded Prediction-Error Image

Zou, D., Shi, Y. B., Su, W., & Xuan, G. (2006) · IEEE International Conference on Multimedia and Expo (ICME) · doi:10.1109/icme.2006.262792 · Cited by 88 · see citing works

Breaking HUGO – The Process Discovery

Fridrich, J., Kodovský, J., Holub, V., & Goljan, M. (2011) · Lecture notes in computer science · doi:10.1007/978-3-642-24178-9_7 · Cited by 68 · see citing works

Steganalysis of spread spectrum data hiding exploiting cover memory

Sullivan, K., Madhow, U., Chandrasekaran, S., & Manjunath, B. S. (2005) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.588121 · Cited by 66 · see citing works

A New Methodology in Steganalysis: Breaking Highly Undetectable Steganograpy (HUGO)

Gül, G., & Kurugöllü, F. (2011) · Lecture notes in computer science · doi:10.1007/978-3-642-24178-9_6 · Cited by 66 · see citing works

Detection of ±1 LSB steganography based on the amplitude of histogram local extrema

Cancelli, G., Doërr, G., Cox, I. J., & Barni, M. (2008) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2008.4711998 · Cited by 61 · see citing works

On dangers of overtraining steganography to incomplete cover model

Kodovský, J., Fridrich, J., & Holub, V. (2011) · doi:10.1145/2037252.2037266 · Cited by 58 · see citing works

On completeness of feature spaces in blind steganalysis

Kodovský, J., & Fridrich, J. (2008) · ACM workshop on Multimedia and security · doi:10.1145/1411328.1411352 · Cited by 41 · see citing works

Feature restoration and distortion metrics

Chonev, V., & Ker, A. D. (2011) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.872574 · Cited by 8 · see citing works

FaceForensics++: Learning to Detect Manipulated Facial Images

Rossler, A., Cozzolino, D., Verdoliva, L., Riess, C., Thies, J., & Niessner, M. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00009 · Cited by 3,314 · see citing works

Universal distortion function for steganography in an arbitrary domain

Holub, V., Fridrich, J., & Denemark, T. (2014) · EURASIP Journal on Information Security · doi:10.1186/1687-417x-2014-1 · Cited by 1,212 · see citing works

Face X-Ray for More General Face Forgery Detection

Li, L., Bao, J., Zhang, T., Yang, H., Chen, D., Wen, F., & Guo, B. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr42600.2020.00505 · Cited by 1,211 · see citing works

Thinking in Frequency: Face Forgery Detection by Mining Frequency-Aware Clues

Qian, Y., Yin, G., Sheng, L., Chen, Z., & Shao, J. (2020) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-58610-2_6 · Cited by 1,058 · see citing works

Deep Residual Network for Steganalysis of Digital Images

Boroumand, M., Chen, M., & Fridrich, J. (2018) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2018.2871749 · Cited by 1,049 · see citing works

Multi-attentional Deepfake Detection

Zhao, H., Wei, T., Zhou, W., Zhang, W., Chen, D., & Yu, N. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr46437.2021.00222 · Cited by 1,019 · see citing works

Designing steganographic distortion using directional filters

Holub, V., & Fridrich, J. (2012) · IEEE International Workshop on Information Forensics and Security · doi:10.1109/wifs.2012.6412655 · Cited by 1,015 · see citing works

Media Forensics and DeepFakes: An Overview

Verdoliva, L. (2020) · IEEE Journal of Selected Topics in Signal Processing · doi:10.1109/jstsp.2020.3002101 · Cited by 979 · see citing works

Capsule-forensics: Using Capsule Networks to Detect Forged Images and Videos

Nguyen, H. H., Yamagishi, J., & Echizen, I. (2019) · ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) · doi:10.1109/icassp.2019.8682602 · Cited by 951 · see citing works

Structural Design of Convolutional Neural Networks for Steganalysis

Xu, G., Wu, H., & Shi, Y.-Q. (2016) · IEEE Signal Processing Letters · doi:10.1109/lsp.2016.2548421 · Cited by 848 · see citing works

A Deep Learning Approach to Universal Image Manipulation Detection Using a New Convolutional Layer

Bayar, B., & Stamm, M. C. (2016) · Proceedings of the 4th ACM Workshop on Information Hiding and Multimedia Security · doi:10.1145/2909827.2930786 · Cited by 838 · see citing works

Deep Learning Hierarchical Representations for Image Steganalysis

Ye, J., Ni, J., & Yi, Y. (2017) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2017.2710946 · Cited by 831 · see citing works

Exploiting Visual Artifacts to Expose Deepfakes and Face Manipulations

Matern, F., Riess, C., & Stamminger, M. (2019) · 2019 IEEE Winter Applications of Computer Vision Workshops (WACVW) · doi:10.1109/wacvw.2019.00020 · Cited by 824 · see citing works

Learning Rich Features for Image Manipulation Detection

Zhou, P., Han, X., Morariu, V. I., & Davis, L. S. (2018) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2018.00116 · Cited by 837 · see citing works

Two-Stream Neural Networks for Tampered Face Detection

Zhou, P., Han, X., Morariu, V. I., & Davis, L. S. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw.2017.229 · Cited by 700 · see citing works

A new cost function for spatial image steganography

Li, B., Wang, M., Huang, J., & Li, X. (2014) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2014.7025854 · Cited by 678 · see citing works

Generalizing Face Forgery Detection with High-frequency Features

Luo, Y., Zhang, Y., Yan, J., & Liu, W. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr46437.2021.01605 · Cited by 609 · see citing works

Constrained Convolutional Neural Networks: A New Approach Towards General Purpose Image Manipulation Detection

Bayar, B., & Stamm, M. C. (2018) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2018.2825953 · Cited by 597 · see citing works

Spatial-Phase Shallow Learning: Rethinking Face Forgery Detection in Frequency Domain

Liu, H., Li, X., Zhou, W., Chen, Y., He, Y., Xue, H., Zhang, W., & Yu, N. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr46437.2021.00083 · Cited by 600 · see citing works

DeeperForensics-1.0: A Large-Scale Dataset for Real-World Face Forgery Detection

Jiang, L., Li, R., Wu, W., Qian, C., & Loy, C. C. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr42600.2020.00296 · Cited by 599 · see citing works

Content-Adaptive Steganography by Minimizing Statistical Detectability

Sedighi, V., Cogranne, R., & Fridrich, J. (2015) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2015.2486744 · Cited by 575 · see citing works

Deep learning for steganalysis via convolutional neural networks

Qian, Y., Dong, J., Wang, W., & Tan, T. (2015) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.2083479 · Cited by 556 · see citing works

Multi-task Learning for Detecting and Segmenting Manipulated Facial Images and Videos

Nguyen, H. H., Fang, F., Yamagishi, J., & Echizen, I. (2019) · 2019 IEEE 10th International Conference on Biometrics Theory, Applications and Systems (BTAS) · doi:10.1109/btas46853.2019.9185974 · Cited by 549 · see citing works

A deep learning approach to detection of splicing and copy-move forgeries in images

Rao, Y., & Ni, J. (2016) · IEEE International Workshop on Information Forensics and Security · doi:10.1109/wifs.2016.7823911 · Cited by 545 · see citing works

Noiseprint: A CNN-Based Camera Model Fingerprint

Cozzolino, D., & Verdoliva, L. (2020) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2019.2916364 · Cited by 499 · see citing works

Two-Branch Recurrent Network for Isolating Deepfakes in Videos

Masi, I., Killekar, A., Mascarenhas, R. M., Gurudatt, S. P., & AbdAlmageed, W. (2020) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-58571-6_39 · Cited by 471 · see citing works

Attributing Fake Images to GANs: Learning and Analyzing GAN Fingerprints

Yu, N., Davis, L. S., & Fritz, M. (2019) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00765 · Cited by 491 · see citing works

Image steganography in spatial domain: A survey

Hussain, M., Wahab, A. W. A., Idris, Y. I. B., Ho, A. T. S., & Jung, K. (2018) · Signal Processing Image Communication · doi:10.1016/j.image.2018.03.012 · Cited by 451 · see citing works

Deep residual learning for image steganalysis

Wu, S., Zhong, S., & Liu, Y. (2018) · Multimedia Tools and Applications · doi:10.1007/s11042-017-4440-4 · Cited by 442 · see citing works

PSCC-Net: Progressive Spatio-Channel Correlation Network for Image Manipulation Detection and Localization

Liu, X., Liu, Y., Chen, J., & Liu, X. (2022) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2022.3189545 · Cited by 435 · see citing works

Low-Complexity Features for JPEG Steganalysis Using Undecimated DCT

Holub, V., & Fridrich, J. (2014) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2014.2364918 · Cited by 431 · see citing works

Towards Universal Fake Image Detectors that Generalize Across Generative Models

Ojha, U., Li, Y., & Lee, Y. J. (2023) · 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr52729.2023.02345 · Cited by 428 · see citing works

Depth-Wise Separable Convolutions and Multi-Level Pooling for an Efficient Spatial CNN-Based Steganalysis

Zhang, R., Zhu, F., Liu, J., & Liu, G. (2019) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2019.2936913 · Cited by 427 · see citing works

Automatic Steganographic Distortion Learning Using a Generative Adversarial Network

Tang, W., Tan, S., Li, B., & Huang, J. (2017) · IEEE Signal Processing Letters · doi:10.1109/lsp.2017.2745572 · Cited by 421 · see citing works

Detection of GAN-Generated Fake Images over Social Networks

Marra, F., Gragnaniello, D., Cozzolino, D., & Verdoliva, L. (2018) · 2018 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR) · doi:10.1109/mipr.2018.00084 · Cited by 399 · see citing works

Selection-channel-aware rich model for Steganalysis of digital images

Denemark, T., Sedighi, V., Holub, V., Cogranne, R., & Fridrich, J. (2014) · IEEE International Workshop on Information Forensics and Security · doi:10.1109/wifs.2014.7084302 · Cited by 391 · see citing works

DeepFake Detection by Analyzing Convolutional Traces

Guarnera, L., Giudice, O., & Battiato, S. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw50498.2020.00341 · Cited by 374 · see citing works

M2TR: Multi-modal Multi-scale Transformers for Deepfake Detection

Wang, J., Wu, Z., Ouyang, W., Han, X., Chen, J., Jiang, Y.-G., & Li, S.-N. (2022) · Proceedings of the 2022 International Conference on Multimedia Retrieval · doi:10.1145/3512527.3531415 · Cited by 368 · see citing works

MVSS-Net: Multi-View Multi-Scale Supervised Networks for Image Manipulation Detection

Dong, C., Chen, X., Hu, R., Cao, J., & Li, X. (2022) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2022.3180556 · Cited by 371 · see citing works

Frequency-aware Discriminative Feature Learning Supervised by Single-Center Loss for Face Forgery Detection

Li, J., Xie, H., Li, J., Wang, Z., & Zhang, Y. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr46437.2021.00639 · Cited by 357 · see citing works

Steganalysis of LSB matching using differences between nonadjacent pixels

Xia, Z., Wang, X., Sun, X., Liu, Q., & Xiong, N. N. (2014) · Multimedia Tools and Applications · doi:10.1007/s11042-014-2381-8 · Cited by 357 · see citing works

Recasting Residual-based Local Descriptors as Convolutional Neural Networks: an Application to Image Forgery Detection

Cozzolino, D., Poggi, G., & Verdoliva, L. (2017) · Proceedings of the 5th ACM Workshop on Information Hiding and Multimedia Security · doi:10.1145/3082031.3083247 · Cited by 349 · see citing works

Digital image steganography using universal distortion

Holub, V., & Fridrich, J. (2013) · ACM Workshop on Information Hiding and Multimedia Security (IH&MMSec) · doi:10.1145/2482513.2482514 · Cited by 348 · see citing works

A Novel Image Steganography Method via Deep Convolutional Generative Adversarial Networks

Hu, D., Wang, L., Jiang, W., Zheng, S., & Li, B. (2018) · IEEE Access · doi:10.1109/access.2018.2852771 · Cited by 342 · see citing works

Detecting GAN generated Fake Images using Co-occurrence Matrices

Nataraj, L., Mohammed, T. M., Manjunath, B. S., Chandrasekaran, S., Flenner, A., Bappy, J. H., & Roy-Chowdhury, A. K. (2019) · Electronic Imaging · doi:10.2352/issn.2470-1173.2019.5.mwsf-532 · Cited by 331 · see citing works

Local Relation Learning for Face Forgery Detection

Chen, S., Yao, T., Chen, Y., Ding, S., Li, J., & Ji, R. (2021) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v35i2.16193 · Cited by 334 · see citing works

A New Payload Partition Strategy in Color Image Steganography

Liao, X., Yu, Y., Li, B., Li, Z., & Qin, Z. (2019) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2019.2896270 · Cited by 330 · see citing works

SPAN: Spatial Pyramid Attention Network for Image Manipulation Localization

Hu, X., Zhang, Z., Jiang, Z., Chaudhuri, S., Yang, Z., & Nevatia, R. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-58589-1_19 · Cited by 329 · see citing works

Yedroudj-Net: An Efficient CNN for Spatial Steganalysis

Yedroudj, M., Comby, F., & Chaumont, M. (2018) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2018.8461438 · Cited by 328 · see citing works

DeepVision: Deepfakes Detection Using Human Eye Blinking Pattern

Jung, T., Kim, S., & Kim, K. (2020) · IEEE Access · doi:10.1109/access.2020.2988660 · Cited by 326 · see citing works

CNN-Based Adversarial Embedding for Image Steganography

Tang, W., Li, B., Tan, S., Barni, M., & Huang, J. (2019) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2019.2891237 · Cited by 316 · see citing works

DeepFake Detection Based on Discrepancies Between Faces and Their Context

Nirkin, Y., Wolf, L., Keller, Y., & Hassner, T. (2022) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2021.3093446 · Cited by 312 · see citing works

A Siamese CNN for Image Steganalysis

You, W., Zhang, H., & Zhao, X. (2020) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2020.3013204 · Cited by 303 · see citing works

Steganalysis of Adaptive JPEG Steganography Using 2D Gabor Filters

Song, X., Liu, F., Yang, C., Luo, X., & Zhang, Y. (2015) · ACM Workshop on Information Hiding and Multimedia Security (IH&MMSec) · doi:10.1145/2756601.2756608 · Cited by 301 · see citing works

Steganalysis of JPEG images using rich models

Kodovský, J., & Fridrich, J. (2012) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.907495 · Cited by 297 · see citing works

Image Manipulation Detection by Multi-View Multi-Scale Supervision

Chen, X., Dong, C., Ji, J., Cao, J., & Li, X. (2021) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv48922.2021.01392 · Cited by 287 · see citing works

Splicebuster: A new blind image splicing detector

Cozzolino, D., Poggi, G., & Verdoliva, L. (2015) · 2015 IEEE International Workshop on Information Forensics and Security (WIFS) · doi:10.1109/wifs.2015.7368565 · Cited by 283 · see citing works

Steganalysis of least significant bit matching using multi‐order differences

Xia, Z., Wang, X., Sun, X., & Wang, B. (2013) · Security and Communication Networks · doi:10.1002/sec.864 · Cited by 277 · see citing works

TruFor: Leveraging All-Round Clues for Trustworthy Image Forgery Detection and Localization

Guillaro, F., Cozzolino, D., Sud, A., Dufour, N., & Verdoliva, L. (2023) · 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr52729.2023.01974 · Cited by 275 · see citing works

First Steps Toward Camera Model Identification With Convolutional Neural Networks

Bondi, L., Baroffio, L., Güera, D., Bestagini, P., Delp, E. J., & Tubaro, S. (2016) · IEEE Signal Processing Letters · doi:10.1109/lsp.2016.2641006 · Cited by 275 · see citing works

An Embedding Cost Learning Framework Using GAN

Yang, J., Ruan, D., Huang, J., Kang, X., & Shi, Y.-Q. (2019) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2019.2922229 · Cited by 271 · see citing works

Random Projections of Residuals for Digital Image Steganalysis

Holub, V., & Fridrich, J. (2013) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2013.2286682 · Cited by 261 · see citing works

SSGAN: Secure Steganography Based on Generative Adversarial Networks

Shi, H., Dong, J., Wang, W., Qian, Y., & Zhang, X. (2018) · Lecture notes in computer science · doi:10.1007/978-3-319-77380-3_51 · Cited by 253 · see citing works

Adaptive Payload Distribution in Multiple Images Steganography Based on Image Texture Features

Liao, X., Yin, J., Chen, M., & Qin, Z. (2020) · IEEE Transactions on Dependable and Secure Computing · doi:10.1109/tdsc.2020.3004708 · Cited by 252 · see citing works

CAT-Net: Compression Artifact Tracing Network for Detection and Localization of Image Splicing

Kwon, M.-J., Yu, I.-J., Nam, S.-H., & Lee, H.-K. (2021) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv48630.2021.00042 · Cited by 253 · see citing works

Invisible steganography via generative adversarial networks

Zhang, R., Dong, S., & Liu, J. (2018) · Multimedia Tools and Applications · doi:10.1007/s11042-018-6951-z · Cited by 250 · see citing works

Moving steganography and steganalysis from the laboratory into the real world

Ker, A. D., Bas, P., Böhme, R., Cogranne, R., Craver, S. A., Filler, T., Fridrich, J., & Pevný, T. (2013) · ACM Workshop on Information Hiding and Multimedia Security (IH&MMSec) · doi:10.1145/2482513.2482965 · Cited by 247 · see citing works

Stacked convolutional auto-encoders for steganalysis of digital images

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Identification of deep network generated images using disparities in color components

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