{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T02:21:48Z","timestamp":1760235708441,"version":"build-2065373602"},"reference-count":40,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2021,9,24]],"date-time":"2021-09-24T00:00:00Z","timestamp":1632441600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61772176","62002103","61976082"],"award-info":[{"award-number":["61772176","62002103","61976082"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Key Scientific and Technological Project of Henan Province","award":["202102210165"],"award-info":[{"award-number":["202102210165"]}]},{"name":"Training Plan of young backbone teachers in colleges and universities of Henan Province","award":["2017GGJS214"],"award-info":[{"award-number":["2017GGJS214"]}]},{"name":"Key Scientific Research Project of Henan Provincial Higher Education","award":["19B510005","20B413004"],"award-info":[{"award-number":["19B510005","20B413004"]}]},{"name":"Key Scientific Research (Soft Science) Project of Higher Education Institu- tions of Henan Province","award":["19A880030"],"award-info":[{"award-number":["19A880030"]}]},{"name":"Key R&amp;D and Promotion Special (Soft Science) Project of Henan Province","award":["202400410088"],"award-info":[{"award-number":["202400410088"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>Fewer contribution feature components in the image high-dimensional steganalysis feature are able to increase the spatio-temporal complexity of detecting the stego images, and even reduce the detection accuracy. In order to maintain or even improve the detection accuracy while effectively reducing the dimension of the DCTR steganalysis feature, this paper proposes a new selection approach for DCTR feature. First, the asymmetric distortion factor and information gain ratio of each feature component are improved to measure the difference between the symmetric cover and stego features, which provides the theoretical basis for selecting the feature components that contribute to a great degree to detecting the stego images. Additionally, the feature components are arranged in descending order rely on the two measurement criteria, which provides the basis for deleting the components. Based on the above, removing feature components that are ranked larger differently according to two criteria. Ultimately, the preserved feature components are used as the final selected feature for training and detection. Comparison experiments with existing classical approaches indicate that this approach can effectively reduce the feature dimension while maintaining or even improving the detection accuracy. At the same time, it can reduce the detection spatio-temporal complexity of the stego images.<\/jats:p>","DOI":"10.3390\/sym13101775","type":"journal-article","created":{"date-parts":[[2021,9,27]],"date-time":"2021-09-27T23:08:31Z","timestamp":1632784111000},"page":"1775","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Gain-Loss Evaluation-Based Generic Selection for Steganalysis Feature"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8610-2013","authenticated-orcid":false,"given":"Ruixia","family":"Jin","sequence":"first","affiliation":[{"name":"SanQuan Medical College, Xinxiang 453003, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2983-8491","authenticated-orcid":false,"given":"Yihao","family":"Wang","sequence":"additional","affiliation":[{"name":"College Software, Henan Normal University, Xinxiang 453007, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8677-516X","authenticated-orcid":false,"given":"Yuanyuan","family":"Ma","sequence":"additional","affiliation":[{"name":"College Computer & Information Engineering, Henan Normal University, Xinxiang 453007, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tao","family":"Li","sequence":"additional","affiliation":[{"name":"College Computer & Information Engineering, Henan Normal University, Xinxiang 453007, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8757-2447","authenticated-orcid":false,"given":"Xintao","family":"Duan","sequence":"additional","affiliation":[{"name":"College Computer & Information Engineering, Henan Normal University, Xinxiang 453007, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,9,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Fridrich, J., Pevn\u00fd, T., and Kodovsk\u00fd, J. (2007, January 20\u201321). Statistically Undetectable JPEG Steganography: Dead Ends, Challenges, and Opportunities. Proceedings of the 9th ACM Multimedia and Security Workshop, Dallas, TX, USA.","DOI":"10.1145\/1288869.1288872"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Sarkar, A., Solanki, K., and Manjunath, B.S. (2008, January 27\u201331). Further Study on YASS: Steganography Based on Randomized Embedding to Resist Blind Steganalysis. Proceedings of the Security, Forensics, Steganography, and Watermarking of Multimedia Contents X, San Jose, CA, USA.","DOI":"10.1117\/12.767893"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Sachnev, V., Kim, H.J., and Zhang, R.Y. (2009, January 7\u20138). Less Detectable JPEG Steganography Method Based on Heuristic Optimization and BCH Syndrome Coding. Proceedings of the 11th ACM Workshop on Multimedia and Security, Princeton, NJ, USA.","DOI":"10.1145\/1597817.1597841"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"705","DOI":"10.1109\/TIFS.2010.2077629","article-title":"Gibbs Construction in Steganography","volume":"5","author":"Filler","year":"2010","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Holub, V., and Fridrich, J. (2012, January 2\u20135). Designing Steganographic Distortion Using Directional Filters. Proceedings of the IEEE Workshop on Information Forensic and Security, Costa Adeje, Spain.","DOI":"10.1109\/WIFS.2012.6412655"},{"key":"ref_6","first-page":"1","article-title":"Universal Distortion Function for Steganography in an Arbitrary Domain","volume":"1","author":"Holub","year":"2014","journal-title":"EURASIP J. Inf. Secur."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"685","DOI":"10.1109\/TCSVT.2019.2896270","article-title":"A New Payload Partition Strategy in Color Image Steganography","volume":"30","author":"Liao","year":"2020","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1109\/TIFS.2015.2486744","article-title":"Content-Adaptive Steganography by Minimizing Statistical Detectability","volume":"11","author":"Sedighi","year":"2016","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"201","DOI":"10.1109\/TIFS.2010.2041812","article-title":"Edge Adaptive Image Steganography Based on LSB Matching Revisited","volume":"5","author":"Luo","year":"2010","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"ref_10","first-page":"1","article-title":"Secure Halftone Image Steganography Based on Feature Space and Layer Embedding","volume":"99","author":"Lu","year":"2020","journal-title":"IEEE Trans. Cybern."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"727","DOI":"10.1016\/j.sigpro.2009.08.010","article-title":"Digital Image Steganography: Survey and Analysis of Current Methods","volume":"90","author":"Cheddad","year":"2010","journal-title":"Signal Process."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1109","DOI":"10.1109\/TCSVT.2012.2224052","article-title":"An Inpainting-Assisted Reversible Steganographic Scheme Using a Histogram Shifting Mechanism","volume":"23","author":"Qin","year":"2013","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"920","DOI":"10.1109\/TIFS.2011.2134094","article-title":"Minimizing Additive Distortion in Steganography Using Syndrome-Trellis Codes","volume":"6","author":"Filler","year":"2011","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"3923","DOI":"10.1109\/TSP.2005.855393","article-title":"Writing on Wet Paper","volume":"53","author":"Fridrich","year":"2005","journal-title":"IEEE Trans. Signal Process."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1138","DOI":"10.1109\/TIFS.2019.2936913","article-title":"Depth-Wise Separable Convolutions and Multi-Level Pooling for an Efficient Spatial CNN-Based Steganalysis","volume":"15","author":"Zhang","year":"2020","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"2545","DOI":"10.1109\/TIFS.2017.2710946","article-title":"Deep Learning Hierarchical Representations for Image Steganalysis","volume":"12","author":"Ye","year":"2017","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1109\/TIP.2002.807363","article-title":"Steganalysis Using Image Quality Metrics","volume":"12","author":"Avcibas","year":"2003","journal-title":"IEEE Trans. Image Process."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1989","DOI":"10.1109\/TCYB.2018.2883082","article-title":"Selection of Robust and Relevant Features for 3-D Steganalysis","volume":"50","author":"Li","year":"2020","journal-title":"IEEE Trans. Cybern."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1747","DOI":"10.1109\/TIFS.2016.2555281","article-title":"Steganalysis Features for Content-Adaptive JPEG Steganography","volume":"11","author":"Denemark","year":"2016","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1404","DOI":"10.1109\/JSAC.2011.110807","article-title":"On the Typical Statistic Features for Image Blind Steganalysis","volume":"29","author":"Luo","year":"2011","journal-title":"IEEE J. Sel. Areas Commun."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"441","DOI":"10.1109\/LSP.2005.847889","article-title":"Steganalysis of LSB Matching in Grayscale Images","volume":"12","author":"Ker","year":"2005","journal-title":"IEEE Signal Process. Lett."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1109\/TIFS.2005.863485","article-title":"Steganalysis Using Higher-order Image Statistics","volume":"1","author":"Lyu","year":"2006","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"ref_23","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":"ref_24","doi-asserted-by":"crossref","first-page":"1007","DOI":"10.1109\/TMM.2005.858377","article-title":"A Feature-based Classification Technique for Blind Image Steganalysis","volume":"7","author":"Lie","year":"2005","journal-title":"IEEE Trans. Multimed."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1109\/TIFS.2006.873595","article-title":"Steganalysis for Markov cover data with applications to images","volume":"1","author":"Sullivan","year":"2006","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"ref_26","first-page":"437","article-title":"Coverless Image Steganography Based on SIFT and BOF","volume":"18","author":"Yuan","year":"2017","journal-title":"J. Internet Technol."},{"key":"ref_27","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":"2015","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Song, X.F., Liu, F.L., and Yang, C.F. (2015, January 17\u201319). Steganalysis of Adaptive JPEG Steganography Using 2D Gabor Filters. Proceedings of the 3rd ACM Workshop on Information Hiding and Multimedia Security, Portland, OR, USA.","DOI":"10.1145\/2756601.2756608"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Kodovsk\u00fd, J., and Fridrich, J. (2012, January 22\u201326). Steganalysis of JPEG Images Using Rich Models. Proceedings of the SPIE, Electronic Imaging, Media Watermarking, Security, and Forensics XIV, Burlingame, CA, USA.","DOI":"10.1117\/12.907495"},{"key":"ref_30","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":"ref_31","unstructured":"Pevn\u00fd, T., and Fridrich, J. (February, January 28). Merging Markov and DCT Features for Multiclass JPEG Steganalysis. Proceedings of the SPIE, Electronic Imaging, Security, Steganography, and Watermarking of Multimedia Contents IX, San Jose, CA, USA."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Kodovsk\u00fd, J., and Fridrich, J. (2009, January 7\u20138). Calibration Revisited. Proceedings of the 11th ACM Multimedia and Security Workshop, Princeton, NJ, USA.","DOI":"10.1145\/1597817.1597830"},{"key":"ref_33","first-page":"033009","article-title":"Principal Feature Selection and Fusion Method for Image Steganalysis","volume":"18","author":"Qin","year":"2008","journal-title":"J. Electron. Imaging"},{"key":"ref_34","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":"2019","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"ref_35","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"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Yang, C.F., Zhang, Y., and Wang, P. (2017, January 19\u201321). Steganalysis Feature Subspace Selection Based on Fisher Criterion. Proceedings of the IEEE International Conference on Data Science and Advanced Analytics, Tokyo, Japan.","DOI":"10.1109\/DSAA.2017.53"},{"key":"ref_37","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":"ref_38","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1109\/79.733495","article-title":"Rate-distortion Methods for Image and Video Compression","volume":"15","author":"Ortega","year":"2002","journal-title":"IEEE Signal Process. Mag."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1016\/j.asoc.2012.07.029","article-title":"Attribute Selection Based on Information Gain Ratio in Fuzzy Rough Set Theory with Application to Tumor Classification","volume":"13","author":"Dai","year":"2013","journal-title":"Appl. Soft Comput."},{"key":"ref_40","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":"Fridrich","year":"2012","journal-title":"IEEE Trans. Inf. Forensics Secur."}],"container-title":["Symmetry"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2073-8994\/13\/10\/1775\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:04:25Z","timestamp":1760166265000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2073-8994\/13\/10\/1775"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,9,24]]},"references-count":40,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2021,10]]}},"alternative-id":["sym13101775"],"URL":"https:\/\/doi.org\/10.3390\/sym13101775","relation":{},"ISSN":["2073-8994"],"issn-type":[{"type":"electronic","value":"2073-8994"}],"subject":[],"published":{"date-parts":[[2021,9,24]]}}}