{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,14]],"date-time":"2026-01-14T18:47:43Z","timestamp":1768416463249,"version":"3.49.0"},"reference-count":46,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2024,7,1]],"date-time":"2024-07-01T00:00:00Z","timestamp":1719792000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2024,7,1]],"date-time":"2024-07-01T00:00:00Z","timestamp":1719792000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2024,7,1]],"date-time":"2024-07-01T00:00:00Z","timestamp":1719792000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2024,7,1]],"date-time":"2024-07-01T00:00:00Z","timestamp":1719792000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2024,7,1]],"date-time":"2024-07-01T00:00:00Z","timestamp":1719792000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,7,1]],"date-time":"2024-07-01T00:00:00Z","timestamp":1719792000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Signal Processing"],"published-print":{"date-parts":[[2024,7]]},"DOI":"10.1016\/j.sigpro.2024.109475","type":"journal-article","created":{"date-parts":[[2024,3,16]],"date-time":"2024-03-16T16:09:37Z","timestamp":1710605377000},"page":"109475","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":4,"special_numbering":"C","title":["Fast dominant feature selection with compensation for efficient image steganalysis"],"prefix":"10.1016","volume":"220","author":[{"given":"Xinquan","family":"Yu","sequence":"first","affiliation":[]},{"given":"Yuanyuan","family":"Ma","sequence":"additional","affiliation":[]},{"given":"Yi","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Xiaolong","family":"Li","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8581-9554","authenticated-orcid":false,"given":"Yao","family":"Zhao","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.sigpro.2024.109475_b1","doi-asserted-by":"crossref","DOI":"10.1016\/j.sigpro.2021.108227","article-title":"Secure halftone image steganography based on density preserving and distortion fusion","volume":"188","author":"Yu","year":"2021","journal-title":"Signal Process."},{"key":"10.1016\/j.sigpro.2024.109475_b2","doi-asserted-by":"crossref","DOI":"10.1016\/j.sigpro.2020.107920","article-title":"Adversarial batch image steganography against CNN-based pooled steganalysis","volume":"181","author":"Li","year":"2021","journal-title":"Signal Process."},{"key":"10.1016\/j.sigpro.2024.109475_b3","article-title":"Digital image steganography survey and investigation (Goal, assessment, method, development, and dataset)","author":"Rustad","year":"2022","journal-title":"Signal Process."},{"key":"10.1016\/j.sigpro.2024.109475_b4","doi-asserted-by":"crossref","DOI":"10.1016\/j.sigpro.2022.108522","article-title":"Sign steganography revisited with robust domain selection","volume":"196","author":"Wu","year":"2022","journal-title":"Signal Process."},{"issue":"2","key":"10.1016\/j.sigpro.2024.109475_b5","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1109\/TIFS.2010.2045842","article-title":"Steganalysis by subtractive pixel adjacency matrix","volume":"5","author":"Pevn\u1ef3","year":"2010","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"10.1016\/j.sigpro.2024.109475_b6","doi-asserted-by":"crossref","unstructured":"J. Kodovsk\u1ef3, J. Fridrich, Calibration revisited, in: Proc. MM&Sec \u201909, 2009, pp. 63\u201374.","DOI":"10.1145\/1597817.1597830"},{"issue":"1","key":"10.1016\/j.sigpro.2024.109475_b7","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/1687-417X-2014-1","article-title":"Universal distortion function for steganography in an arbitrary domain","volume":"2014","author":"Holub","year":"2014","journal-title":"Eurasip J. Inf. Secur."},{"key":"10.1016\/j.sigpro.2024.109475_b8","doi-asserted-by":"crossref","unstructured":"J. Fridrich, T. Pevn\u1ef3, J. Kodovsk\u1ef3, Statistically undetectable JPEG steganography: dead ends challenges, and opportunities, in: Proc. MM&Sec \u201907, 2007, pp. 3\u201314.","DOI":"10.1145\/1288869.1288872"},{"issue":"10","key":"10.1016\/j.sigpro.2024.109475_b9","doi-asserted-by":"crossref","first-page":"2274","DOI":"10.1109\/TCSVT.2016.2587388","article-title":"Decomposing joint distortion for adaptive steganography","volume":"27","author":"Zhang","year":"2016","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.sigpro.2024.109475_b10","doi-asserted-by":"crossref","DOI":"10.1016\/j.sigpro.2022.108711","article-title":"The infinite race between steganography and steganalysis in images","author":"Muralidharan","year":"2022","journal-title":"Signal Process."},{"issue":"24","key":"10.1016\/j.sigpro.2024.109475_b11","doi-asserted-by":"crossref","first-page":"26391","DOI":"10.1007\/s11042-016-4157-9","article-title":"2D Gabor filters-based steganalysis of content-adaptive JPEG steganography","volume":"76","author":"Song","year":"2017","journal-title":"Multimed. Tools Appl."},{"key":"10.1016\/j.sigpro.2024.109475_b12","doi-asserted-by":"crossref","unstructured":"J. Kodovsk\u1ef3, J. Fridrich, Steganalysis of JPEG images using rich models, in: Proc. Media Watermarking, Security, and Forensics 2012, Vol. 8303, 2012, p. 83030A.","DOI":"10.1117\/12.907495"},{"issue":"2","key":"10.1016\/j.sigpro.2024.109475_b13","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1109\/TIFS.2014.2364918","article-title":"Low-complexity features for JPEG steganalysis using undecimated DCT","volume":"10","author":"Holub","year":"2014","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"issue":"3","key":"10.1016\/j.sigpro.2024.109475_b14","doi-asserted-by":"crossref","first-page":"868","DOI":"10.1109\/TIFS.2012.2190402","article-title":"Rich models for steganalysis of digital images","volume":"7","author":"Fridrich","year":"2012","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"10.1016\/j.sigpro.2024.109475_b15","doi-asserted-by":"crossref","DOI":"10.1016\/j.sigpro.2019.107422","article-title":"Towards feature representation for steganalysis of spatial steganography","volume":"169","author":"Wang","year":"2020","journal-title":"Signal Process."},{"key":"10.1016\/j.sigpro.2024.109475_b16","doi-asserted-by":"crossref","DOI":"10.1016\/j.sigpro.2020.107576","article-title":"Deep residual network for halftone image steganalysis with stego-signal diffusion","volume":"172","author":"Zeng","year":"2020","journal-title":"Signal Process."},{"issue":"9","key":"10.1016\/j.sigpro.2024.109475_b17","doi-asserted-by":"crossref","first-page":"3081","DOI":"10.1109\/TCSVT.2019.2936028","article-title":"Binary image steganalysis based on histogram of structuring elements","volume":"30","author":"Lu","year":"2020","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"issue":"11","key":"10.1016\/j.sigpro.2024.109475_b18","doi-asserted-by":"crossref","first-page":"4100","DOI":"10.1109\/TCSVT.2019.2954041","article-title":"Improved JPEG phase-aware steganalysis features using multiple filter sizes and difference images","volume":"30","author":"Xia","year":"2020","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"issue":"2","key":"10.1016\/j.sigpro.2024.109475_b19","doi-asserted-by":"crossref","first-page":"336","DOI":"10.1109\/TCSVT.2018.2799243","article-title":"Selection of rich model steganalysis features based on decision rough set \u03b1-positive region reduction","volume":"29","author":"Ma","year":"2018","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.sigpro.2024.109475_b20","doi-asserted-by":"crossref","first-page":"214","DOI":"10.1016\/j.ins.2020.02.070","article-title":"Low-rank matrix regression for image feature extraction and feature selection","volume":"522","author":"Yuan","year":"2020","journal-title":"Inform. Sci."},{"key":"10.1016\/j.sigpro.2024.109475_b21","doi-asserted-by":"crossref","unstructured":"C. Yang, Y. Zhang, P. Wang, X. Luo, F. Liu, J. Lu, Steganalysis feature subspace selection based on Fisher criterion, in: Proc. IEEE DSAA 2017, 2017, pp. 514\u2013521.","DOI":"10.1109\/DSAA.2017.53"},{"key":"10.1016\/j.sigpro.2024.109475_b22","first-page":"724","article-title":"W2ID criterion-based rich model steganalysis features selection","volume":"44","author":"Ma","year":"2021","journal-title":"Chinese J. Comput."},{"key":"10.1016\/j.sigpro.2024.109475_b23","doi-asserted-by":"crossref","first-page":"55063","DOI":"10.1109\/ACCESS.2020.2981738","article-title":"A multi-scale feature selection method for steganalytic feature GFR","volume":"8","author":"Yu","year":"2020","journal-title":"IEEE Access"},{"key":"10.1016\/j.sigpro.2024.109475_b24","doi-asserted-by":"crossref","DOI":"10.1016\/j.ins.2023.118973","article-title":"Adaptive feature selection for image steganalysis based on classification metrics","volume":"644","author":"Ma","year":"2023","journal-title":"Inform. Sci."},{"key":"10.1016\/j.sigpro.2024.109475_b25","doi-asserted-by":"crossref","unstructured":"G. Xuan, X. Zhu, P. Chai, Z. Zhang, Y.Q. Shi, D. Fu, Feature selection based on the Bhattacharyya distance, in: Proc. ICPR\u201906, Vol. 4, 2006, pp. 957\u2013957.","DOI":"10.1109\/ICPR.2006.557"},{"key":"10.1016\/j.sigpro.2024.109475_b26","doi-asserted-by":"crossref","unstructured":"J.L. Davidson, J. Jalan, Feature selection for steganalysis using the Mahalanobis distance, in: Proc. Media Forensics and Security II, Vol. 7541, 2010, pp. 26\u201337.","DOI":"10.1117\/12.841074"},{"key":"10.1016\/j.sigpro.2024.109475_b27","doi-asserted-by":"crossref","first-page":"4244","DOI":"10.1109\/ACCESS.2019.2963084","article-title":"Feature selection for image steganalysis using binary bat algorithm","volume":"8","author":"Liu","year":"2019","journal-title":"IEEE Access"},{"key":"10.1016\/j.sigpro.2024.109475_b28","doi-asserted-by":"crossref","first-page":"154418","DOI":"10.1109\/ACCESS.2020.3018709","article-title":"Comprehensive criteria-based generalized steganalysis feature selection method","volume":"8","author":"Wang","year":"2020","journal-title":"IEEE Access"},{"issue":"1","key":"10.1016\/j.sigpro.2024.109475_b29","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1016\/j.diin.2013.12.001","article-title":"Selection of image features for steganalysis based on the Fisher criterion","volume":"11","author":"Lu","year":"2014","journal-title":"Digit. Investig."},{"key":"10.1016\/j.sigpro.2024.109475_b30","doi-asserted-by":"crossref","unstructured":"J.L. Davidson, J. Jalan, Feature selection for steganalysis using the Mahalanobis distance, in: Proc. Media Forensics and Security II, Vol. 7541, 2010, 754104.","DOI":"10.1117\/12.841074"},{"key":"10.1016\/j.sigpro.2024.109475_b31","doi-asserted-by":"crossref","unstructured":"Y. Zhang, F. Liu, H. Jia, J. Lu, C. Yang, Optimization of rich model based on Fisher criterion for image steganalysis, in: Proc. ICACI 2018, 2018, pp. 187\u2013192.","DOI":"10.1109\/ICACI.2018.8377604"},{"key":"10.1016\/j.sigpro.2024.109475_b32","first-page":"1","article-title":"Steganalysis feature selection with multidimensional evaluation & dynamic threshold allocation","author":"Ma","year":"2023","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"issue":"12","key":"10.1016\/j.sigpro.2024.109475_b33","doi-asserted-by":"crossref","first-page":"1996","DOI":"10.1109\/TIFS.2013.2286682","article-title":"Random projections of residuals for digital image steganalysis","volume":"8","author":"Holub","year":"2013","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"10.1016\/j.sigpro.2024.109475_b34","doi-asserted-by":"crossref","unstructured":"T. Denemark, V. Sedighi, V. Holub, R. Cogranne, J. Fridrich, Selection-channel-aware rich model for steganalysis of digital images, in: Proc. WIFS 2014, 2014, pp. 48\u201353.","DOI":"10.1109\/WIFS.2014.7084302"},{"key":"10.1016\/j.sigpro.2024.109475_b35","doi-asserted-by":"crossref","unstructured":"S. Tan, B. Li, Stacked convolutional auto-encoders for steganalysis of digital images, in: Proc. APSIPA 2014, 2014, pp. 1\u20134.","DOI":"10.1109\/APSIPA.2014.7041565"},{"issue":"5","key":"10.1016\/j.sigpro.2024.109475_b36","doi-asserted-by":"crossref","first-page":"708","DOI":"10.1109\/LSP.2016.2548421","article-title":"Structural design of convolutional neural networks for steganalysis","volume":"23","author":"Xu","year":"2016","journal-title":"IEEE Signal Process. Lett."},{"issue":"5","key":"10.1016\/j.sigpro.2024.109475_b37","doi-asserted-by":"crossref","first-page":"1181","DOI":"10.1109\/TIFS.2018.2871749","article-title":"Deep residual network for steganalysis of digital images","volume":"14","author":"Boroumand","year":"2018","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"10.1016\/j.sigpro.2024.109475_b38","doi-asserted-by":"crossref","unstructured":"Y. Yousfi, J. Butora, E. Khvedchenya, J. Fridrich, ImageNet pre-trained CNNs for JPEG steganalysis, in: Proc. WIFS 2020, 2020, pp. 1\u20136.","DOI":"10.1109\/WIFS49906.2020.9360897"},{"key":"10.1016\/j.sigpro.2024.109475_b39","doi-asserted-by":"crossref","unstructured":"G. Xu, Deep convolutional neural network to detect J-UNIWARD, in: Proc. IH&MMSec 2017, 2017, pp. 67\u201373.","DOI":"10.1145\/3082031.3083236"},{"issue":"5","key":"10.1016\/j.sigpro.2024.109475_b40","doi-asserted-by":"crossref","first-page":"1200","DOI":"10.1109\/TIFS.2017.2779446","article-title":"Large-scale JPEG image steganalysis using hybrid deep-learning framework","volume":"13","author":"Zeng","year":"2017","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"10.1016\/j.sigpro.2024.109475_b41","doi-asserted-by":"crossref","first-page":"1287","DOI":"10.1109\/LSP.2023.3313517","article-title":"Image steganalysis network based on dual-attention mechanism","volume":"30","author":"Zhang","year":"2023","journal-title":"IEEE Signal Process. Lett."},{"key":"10.1016\/j.sigpro.2024.109475_b42","doi-asserted-by":"crossref","first-page":"987","DOI":"10.1109\/LSP.2023.3300792","article-title":"Image steganalysis against adversarial steganography by combining confidence and pixel artifacts","volume":"30","author":"Hu","year":"2023","journal-title":"IEEE Signal Process. Lett."},{"issue":"2","key":"10.1016\/j.sigpro.2024.109475_b43","doi-asserted-by":"crossref","first-page":"1355","DOI":"10.3934\/mbe.2020068","article-title":"Image steganalysis feature selection based on the improved Fisher criterion","volume":"17","author":"Ma","year":"2020","journal-title":"Math. Biosci. Eng."},{"key":"10.1016\/j.sigpro.2024.109475_b44","doi-asserted-by":"crossref","unstructured":"P. Bas, T. Filler, T. Pevn\u1ef3, \u2018Break our steganographic system\u2019: the ins and outs of organizing BOSS, in: Proc. IH 2011, 2011, pp. 59\u201370.","DOI":"10.1007\/978-3-642-24178-9_5"},{"key":"10.1016\/j.sigpro.2024.109475_b45","doi-asserted-by":"crossref","unstructured":"R. Cogranne, Q. Giboulot, P. Bas, ALASKA# 2: Challenging academic research on steganalysis with realistic images, in: Proc. WIFS 2020, 2020, pp. 1\u20135.","DOI":"10.1109\/WIFS49906.2020.9360896"},{"issue":"2","key":"10.1016\/j.sigpro.2024.109475_b46","doi-asserted-by":"crossref","first-page":"432","DOI":"10.1109\/TIFS.2011.2175919","article-title":"Ensemble classifiers for steganalysis of digital media","volume":"7","author":"Kodovsk\u1ef3","year":"2011","journal-title":"IEEE Trans. Inf. Forensics Secur."}],"container-title":["Signal Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S016516842400094X?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S016516842400094X?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2024,11,14]],"date-time":"2024-11-14T12:32:37Z","timestamp":1731587557000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S016516842400094X"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,7]]},"references-count":46,"alternative-id":["S016516842400094X"],"URL":"https:\/\/doi.org\/10.1016\/j.sigpro.2024.109475","relation":{},"ISSN":["0165-1684"],"issn-type":[{"value":"0165-1684","type":"print"}],"subject":[],"published":{"date-parts":[[2024,7]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Fast dominant feature selection with compensation for efficient image steganalysis","name":"articletitle","label":"Article Title"},{"value":"Signal Processing","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.sigpro.2024.109475","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2024 Elsevier B.V. All rights reserved.","name":"copyright","label":"Copyright"}],"article-number":"109475"}}