This is a preview of subscription content, log in to check access.
Buy single article
Instant access to the full article PDF.
Price includes VAT for USA
Li H D, Luo W Q, Qiu X Q, et al. Identification of various image operations using residual-based features. IEEE Trans Circuits Syst Video Technol, 2018, 28: 31–45
Chen J S, Kang X G, Liu Y, et al. Median filtering forensics based on convolutional neural networks. IEEE Signal Process Lett, 2015, 22: 1849–1853
Bayar B, Stamm M C. A deep learning approach to universal image manipulation detection using a new convolutional layer. In: Proceedings of ACM Workshop on Information Hiding and Multimedia Security, Vigo, 2016. 5–10
Xu G S, Wu H Z, Shi Y Q. Structural design of convolutional neural networks for steganalysis. IEEE Signal Process Lett, 2016, 23: 708–712
Bas P, Filler T, Pevný T. “Break our steganographic system”: the ins and outs of organizing BOSS. Inf Hiding, 2011, 6958: 59–70
This work was supported in part by National Natural Science Foundation of China (Grant Nos. 61672551, 61602318), Special Research Plan of Guangdong Province (Grant No. 2015TQ01X365), Guangzhou Science and Technology Plan Project (Grant No. 201707010167), Shenzhen R&D Program (Grant No. JCYJ20160328144421330), and Alibaba Group through Alibaba Innovative Research Program.
About this article
Cite this article
Chen, B., Li, H., Luo, W. et al. Image processing operations identification via convolutional neural network. Sci. China Inf. Sci. 63, 139109 (2020). https://doi.org/10.1007/s11432-018-9492-6