{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,2]],"date-time":"2026-08-02T04:20:51Z","timestamp":1785644451891,"version":"3.56.0"},"reference-count":113,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,8,12]],"date-time":"2024-08-12T00:00:00Z","timestamp":1723420800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2024,8,12]],"date-time":"2024-08-12T00:00:00Z","timestamp":1723420800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"DOI":"10.13039\/501100007601","name":"Horizon 2020","doi-asserted-by":"publisher","award":["101021687"],"award-info":[{"award-number":["101021687"]}],"id":[{"id":"10.13039\/501100007601","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100007601","name":"Horizon 2020","doi-asserted-by":"publisher","award":["101021687"],"award-info":[{"award-number":["101021687"]}],"id":[{"id":"10.13039\/501100007601","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["EURASIP J. on Info. Security"],"DOI":"10.1186\/s13635-024-00171-6","type":"journal-article","created":{"date-parts":[[2024,8,12]],"date-time":"2024-08-12T04:02:35Z","timestamp":1723435355000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Cover-source mismatch in steganalysis: systematic review"],"prefix":"10.1186","volume":"2024","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-0479-564X","authenticated-orcid":false,"given":"Antoine","family":"Mallet","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Martin","family":"Bene\u0161","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"R\u00e9mi","family":"Cogranne","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,8,12]]},"reference":[{"key":"171_CR1","doi-asserted-by":"crossref","unstructured":"R.\u00a0Abecidan, V.\u00a0Itier, J.\u00a0Boulanger, P.\u00a0Bas, in WIFS, Unsupervised JPEG domain adaptation for practical digital image forensics (IEEE, 2021), pp. 1\u20136","DOI":"10.1109\/WIFS53200.2021.9648397"},{"key":"171_CR2","unstructured":"R.\u00a0Abecidan, V.\u00a0Itier, J.\u00a0Boulanger, P.\u00a0Bas, in XXIX\u00e8me Colloque Francophone de Traitement du Signal et des Images-GRETSI\u201923, Recherche et Analyse de Sources Repr\u00e9sentatives pour la St\u00e9ganalyse (Grenoble, 2023). https:\/\/hal.science\/hal-04166647"},{"key":"171_CR3","doi-asserted-by":"crossref","unstructured":"R.\u00a0Abecidan, V.\u00a0Itier, J.\u00a0Boulanger, P.\u00a0Bas, T.\u00a0Pevn\u00fd, in WIFS, Leveraging data geometry to mitigate CSM in steganalysis (IEEE, 2023), pp. 1\u20135","DOI":"10.1109\/WIFS58808.2023.10374944"},{"key":"171_CR4","doi-asserted-by":"crossref","unstructured":"R.\u00a0Abecidan, V.\u00a0Itier, J.\u00a0Boulanger, P.\u00a0Bas, T.\u00a0Pevn\u00fd, in WIFS, Using set covering to generate databases for holistic steganalysis (IEEE, 2022), pp. 1\u20136","DOI":"10.1109\/WIFS55849.2022.9975430"},{"key":"171_CR5","doi-asserted-by":"crossref","unstructured":"M.\u00a0Barni, G.\u00a0Cancelli, A.\u00a0Esposito, in ICASSP, Forensics-aided steganalysis of heterogeneous images (IEEE, 2010), pp. 1690\u20131693","DOI":"10.1109\/ICASSP.2010.5495494"},{"key":"171_CR6","doi-asserted-by":"crossref","unstructured":"P.\u00a0Bas, T.\u00a0Filler, T.\u00a0Pevn\u00fd, in IH, \u201cBreak Our Steganographic System\u201d: the ins and outs of organizing BOSS (Springer, 2011), pp. 59\u201370","DOI":"10.1007\/978-3-642-24178-9_5"},{"key":"171_CR7","doi-asserted-by":"crossref","unstructured":"M.\u00a0Bene\u0161, N.\u00a0Hofer, R.\u00a0B\u00f6hme, in EUSIPCO, The effect of the JPEG implementation on the cover-source mismatch error in image steganalysis (IEEE, 2022), pp. 1057\u20131061","DOI":"10.23919\/EUSIPCO55093.2022.9909711"},{"key":"171_CR8","unstructured":"J.\u00a0Blitzer, M.\u00a0Dredze, F.\u00a0Pereira, in ACL, Biographies, bollywood, boom-boxes and blenders: domain adaptation for sentiment classification,\u00a0Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics\u00a0(Association for Computational Linguistics,\u00a0Prague, 2007), pp. 440\u2013447. https:\/\/aclanthology.org\/P07-1056"},{"key":"171_CR9","doi-asserted-by":"crossref","unstructured":"D.\u00a0Borghys, P.\u00a0Bas, H.\u00a0Bruyninckx, in IH&MMSec, Facing the cover-source mismatch on JPHide using training-set design (ACM, 2018), pp. 17\u201322","DOI":"10.1145\/3206004.3206021"},{"key":"171_CR10","doi-asserted-by":"crossref","unstructured":"M.\u00a0Boroumand, J.\u00a0Fridrich, Scalable processing history detector for JPEG images. EI 29, 128\u2013137 (2017)","DOI":"10.2352\/ISSN.2470-1173.2017.7.MWSF-336"},{"issue":"5","key":"171_CR11","first-page":"1181","volume":"14","author":"M Boroumand","year":"2018","unstructured":"M. Boroumand, M. Chen, J. Fridrich, Deep residual network for steganalysis of digital images. TIFS 14(5), 1181\u20131193 (2018)","journal-title":"TIFS"},{"key":"171_CR12","doi-asserted-by":"crossref","unstructured":"J.\u00a0Butora, J.\u00a0Fridrich, Detection of diversified stego sources with CNNs. EI 31, 1\u201311 (2019)","DOI":"10.2352\/ISSN.2470-1173.2019.5.MWSF-534"},{"key":"171_CR13","doi-asserted-by":"crossref","unstructured":"C.\u00a0Cachin, in IH, An information-theoretic model for steganography (Springer, 1998), pp. 306\u2013318","DOI":"10.1007\/3-540-49380-8_21"},{"key":"171_CR14","doi-asserted-by":"crossref","unstructured":"G.\u00a0Cancelli, G.\u00a0Do\u00ebrr, M.\u00a0Barni, I.\u00a0Cox, in MMSP, A comparative study of $$\\pm 1$$\u00a0steganalyzers (IEEE, 2008), pp. 791\u2013796","DOI":"10.1109\/MMSP.2008.4665182"},{"key":"171_CR15","doi-asserted-by":"crossref","unstructured":"M.\u00a0Chen, V.\u00a0Sedighi, M.\u00a0Boroumand, J.\u00a0Fridrich, in IH&MMSec, JPEG-phase-aware convolutional neural network for steganalysis of JPEG images (ACM, 2017), pp. 75\u201384","DOI":"10.1145\/3082031.3083248"},{"key":"171_CR16","doi-asserted-by":"crossref","unstructured":"R.\u00a0Cogranne, in WIFS, A sequential method for online steganalysis (IEEE, 2015), pp. 1\u20136","DOI":"10.1109\/WIFS.2015.7368596"},{"key":"171_CR17","doi-asserted-by":"crossref","unstructured":"R.\u00a0Cogranne, Q.\u00a0Giboulot, P.\u00a0Bas, in IH &MMSec, The ALASKA steganalysis challenge: a first step towards steganalysis (ACM, 2019), pp. 125\u2013137","DOI":"10.1145\/3335203.3335726"},{"key":"171_CR18","doi-asserted-by":"crossref","unstructured":"R.\u00a0Cogranne, Q.\u00a0Giboulot, P.\u00a0Bas, in WIFS, ALASKA#2: challenging academic research on steganalysis with realistic images (IEEE, 2020), pp. 1\u20135","DOI":"10.1109\/WIFS49906.2020.9360896"},{"key":"171_CR19","doi-asserted-by":"crossref","unstructured":"R.\u00a0Cogranne, V.\u00a0Sedighi, J.\u00a0Fridrich, in ICASSP, Practical strategies for content-adaptive batch steganography and pooled steganalysis (IEEE, 2017), pp. 2122\u20132126","DOI":"10.1109\/ICASSP.2017.7952531"},{"key":"171_CR20","doi-asserted-by":"crossref","unstructured":"R.\u00a0Cogranne, V.\u00a0Sedighi, J.\u00a0Fridrich, T.\u00a0Pevn\u00fd, in IEEE International Workshop on Information Forensics and Security (WIFS), Is ensemble classifier needed for steganalysis in high-dimensional feature spaces? (IEEE, 2015)","DOI":"10.1109\/WIFS.2015.7368597"},{"issue":"12","key":"171_CR21","first-page":"2627","volume":"10","author":"R Cogranne","year":"2015","unstructured":"R. Cogranne, J. Fridrich, Modeling and extending the ensemble classifier for steganalysis of digital images using hypothesis testing theory. TIFS 10(12), 2627\u20132642 (2015)","journal-title":"TIFS"},{"issue":"8","key":"171_CR22","first-page":"1736","volume":"11","author":"TD Denemark","year":"2016","unstructured":"T.D. Denemark, M. Boroumand, J. Fridrich, Steganalysis features for content-adaptive JPEG steganography. TIFS 11(8), 1736\u20131746 (2016)","journal-title":"TIFS"},{"key":"171_CR23","doi-asserted-by":"crossref","unstructured":"C.\u00a0Feng, X.\u00a0Kong, M.\u00a0Li, Y.\u00a0Yang, Y.\u00a0Guo, in ICIP, Contribution-based feature transfer for JPEG mismatched steganalysis (IEEE, 2017), pp. 500\u2013504","DOI":"10.1109\/ICIP.2017.8296331"},{"key":"171_CR24","doi-asserted-by":"crossref","unstructured":"J.\u00a0Fridrich, Steganography in Digital Media: Principles, Algorithms, and Applications (Cambridge University Press, 2009)","DOI":"10.1017\/CBO9781139192903"},{"key":"171_CR25","doi-asserted-by":"crossref","unstructured":"J.\u00a0Fridrich, J.\u00a0Kodovsk\u00fd, V.\u00a0Holub, M.\u00a0Goljan, in IH, Breaking HUGO\u2013the process discovery (Springer, 2011), pp. 85\u2013101","DOI":"10.1007\/978-3-642-24178-9_7"},{"key":"171_CR26","doi-asserted-by":"crossref","unstructured":"Q.\u00a0Giboulot, P.\u00a0Bas, R.\u00a0Cogranne, D.\u00a0Borghys, in EUSIPCO, The cover source mismatch problem in deep-learning steganalysis (IEEE, 2022), pp. 1032\u20131036","DOI":"10.23919\/EUSIPCO55093.2022.9909553"},{"key":"171_CR27","doi-asserted-by":"crossref","unstructured":"Q.\u00a0Giboulot, R.\u00a0Cogranne, P.\u00a0Bas, in MWSF, Steganalysis into the wild: how to define a source? vol.\u00a030 (SPIE, 2018), pp. 1\u201312","DOI":"10.2352\/ISSN.2470-1173.2018.07.MWSF-318"},{"key":"171_CR28","first-page":"115888","volume":"86","author":"Q Giboulot","year":"2020","unstructured":"Q. Giboulot, R. Cogranne, D. Borghys, P. Bas, Effects and solutions of cover-source mismatch in image steganalysis. SPIC 86, 115888 (2020)","journal-title":"SPIC"},{"key":"171_CR29","first-page":"4436","volume":"18","author":"Q Giboulot","year":"2023","unstructured":"Q. Giboulot, T. Pevn\u00fd, A. Ker, The non-zero-sum game of steganography in heterogeneous environments. TIFS 18, 4436\u20134448 (2023)","journal-title":"TIFS"},{"key":"171_CR30","doi-asserted-by":"crossref","unstructured":"M.\u00a0Goljan, J.\u00a0Fridrich, T.\u00a0Holotyak, in SSWMC, New blind steganalysis and its implications, vol. 6072 (SPIE, 2006), p. 607201","DOI":"10.1117\/12.643254"},{"key":"171_CR31","doi-asserted-by":"crossref","unstructured":"F.K. Gomis, M.S. Camara, I.\u00a0Diop, S.M. Farssi, K.\u00a0Tall, B.\u00a0Diouf, in ISCV, Multiple linear regression for universal steganalysis of images (IEEE, 2018), pp. 1\u20134","DOI":"10.1109\/ISACV.2018.8354060"},{"issue":"3","key":"171_CR32","doi-asserted-by":"publisher","first-page":"261","DOI":"10.1016\/0167-6393(94)00059-J","volume":"16","author":"Y Gong","year":"1995","unstructured":"Y. Gong, Speech recognition in noisy environments: a survey. Speech Commun. 16(3), 261\u2013291 (1995)","journal-title":"Speech Commun."},{"issue":"3","key":"171_CR33","first-page":"1173","volume":"69","author":"H Guan","year":"2021","unstructured":"H. Guan, M. Liu, Domain adaptation for medical image analysis: a survey. TBME 69(3), 1173\u20131185 (2021)","journal-title":"TBME"},{"key":"171_CR34","doi-asserted-by":"crossref","unstructured":"H. Guan, M. Liu, Domain adaptation for medical image analysis: a survey. TBME 69(3), 1173--1185 (2022)","DOI":"10.1109\/TBME.2021.3117407"},{"key":"171_CR35","unstructured":"K.\u00a0Hirakawa, F.\u00a0Baqai, Digital camera processing pipeline. The Wiley-IS &T Series in Imaging Science and Technology (Wiley, 2023)"},{"issue":"2","key":"171_CR36","first-page":"219","volume":"10","author":"V Holub","year":"2014","unstructured":"V. Holub, J. Fridrich, Low-complexity features for JPEG steganalysis using undecimated DCT. TIFS 10(2), 219\u2013228 (2014)","journal-title":"TIFS"},{"key":"171_CR37","doi-asserted-by":"crossref","unstructured":"X.\u00a0Hou, T.\u00a0Zhang, G.\u00a0Xiong, B.\u00a0Wan, in MINES, Forensics-aided steganalysis of heterogeneous bitmap images with different compression history (IEEE, 2012), pp. 874\u2013877","DOI":"10.3837\/tiis.2012.08.003"},{"issue":"3","key":"171_CR38","first-page":"385","volume":"29","author":"X Hou","year":"2014","unstructured":"X. Hou, T. Zhang, G. Xiong, Z. Lu, K. Xie, A novel steganalysis framework of heterogeneous images based on GMM clustering. SPIC 29(3), 385\u2013399 (2014)","journal-title":"SPIC"},{"key":"171_CR39","first-page":"72","volume":"47","author":"X Hou","year":"2016","unstructured":"X. Hou, T. Zhang, C. Xu, New framework for unsupervised universal steganalysis via SRISP-aided outlier detection. SPIC 47, 72\u201385 (2016)","journal-title":"SPIC"},{"key":"171_CR40","doi-asserted-by":"crossref","unstructured":"D.\u00a0Hu, Z.\u00a0Ma, Y.\u00a0Fan, L.\u00a0Wang, in IWDW, A study of the two-way effects of cover-source mismatch and texture complexity in steganalysis (Springer, 2017), pp. 601\u2013615","DOI":"10.1007\/978-3-319-53465-7_45"},{"key":"171_CR41","first-page":"7643","volume":"78","author":"D Hu","year":"2019","unstructured":"D. Hu, Z. Ma, Y. Fan, S. Zheng, D. Ye, L. Wang, Study on the interaction between the cover-source mismatch and texture complexity in steganalysis. MTAP 78, 7643\u20137666 (2019)","journal-title":"MTAP"},{"issue":"3","key":"171_CR42","first-page":"1228","volume":"14","author":"I Hussain","year":"2020","unstructured":"I. Hussain, J. Zeng, X. Qin, S. Tan, A survey on deep convolutional neural networks for image steganography and steganalysis. TIIS 14(3), 1228\u20131248 (2020)","journal-title":"TIIS"},{"key":"171_CR43","doi-asserted-by":"publisher","first-page":"107105","DOI":"10.1016\/j.patcog.2019.107105","volume":"100","author":"J Jia","year":"2020","unstructured":"J. Jia, L. Zhai, W. Ren, L. Wang, Y. Ren, L. Zhang, Transferable heterogeneous feature subspace learning for JPEG mismatched steganalysis. Pattern Recognit. 100, 107105 (2020)","journal-title":"Pattern Recognit."},{"key":"171_CR44","unstructured":"S.\u00a0Katzenbeisser, F.\u00a0Petitcolas, Information Hiding (Artech house, 2016)"},{"key":"171_CR45","doi-asserted-by":"crossref","unstructured":"E.\u00a0Kaziakhmedov, E.\u00a0Dworetzky, J.\u00a0Fridrich, in WIFS, Observing bag gain in JPEG batch steganography (IEEE, 2023)","DOI":"10.1109\/WIFS58808.2023.10374876"},{"key":"171_CR46","doi-asserted-by":"crossref","unstructured":"A.\u00a0Ker, in IH, Batch steganography and pooled steganalysis (Springer, 2006), pp. 265\u2013281","DOI":"10.1007\/978-3-540-74124-4_18"},{"key":"171_CR47","doi-asserted-by":"crossref","unstructured":"A.\u00a0Ker, P.\u00a0Bas, R.\u00a0B\u00f6hme, R.\u00a0Cogranne, S.\u00a0Craver, T.\u00a0Filler, J.\u00a0Fridrich, T.\u00a0Pevn\u00fd, in IH&MMSec, Moving steganography and steganalysis from the laboratory into the real world (ACM, 2013), pp. 45\u201358","DOI":"10.1145\/2482513.2482965"},{"key":"171_CR48","doi-asserted-by":"crossref","unstructured":"A.\u00a0Ker, T.\u00a0Pevn\u00fd, in MMSec, Batch steganography in the real world (ACM, 2012), pp. 1\u201310","DOI":"10.1145\/2361407.2361409"},{"key":"171_CR49","doi-asserted-by":"crossref","unstructured":"A.\u00a0Ker, T.\u00a0Pevn\u00fd, in MWSF, A mishmash of methods for mitigating the model mismatch mess, vol. 9028 (SPIE, 2014), pp. 189\u2013203","DOI":"10.1117\/12.2038908"},{"key":"171_CR50","doi-asserted-by":"crossref","unstructured":"A.\u00a0Ker, T.\u00a0Pevn\u00fd, in MWSF, A new paradigm for steganalysis via clustering, vol. 7880 (SPIE, 2011), pp. 312\u2013324","DOI":"10.1117\/12.872888"},{"key":"171_CR51","doi-asserted-by":"crossref","unstructured":"A.\u00a0Ker, T.\u00a0Pevn\u00fd, in MWSF, Identifying a steganographer in realistic and heterogeneous data sets, vol. 8303 (SPIE, 2012), pp. 182\u2013194","DOI":"10.1117\/12.910565"},{"issue":"6","key":"171_CR52","doi-asserted-by":"publisher","first-page":"441","DOI":"10.1109\/LSP.2005.847889","volume":"12","author":"A Ker","year":"2005","unstructured":"A. Ker, Steganalysis of LSB matching in grayscale images. Sig. Process. Lett. 12(6), 441\u2013444 (2005)","journal-title":"Sig. Process. Lett."},{"issue":"9","key":"171_CR53","first-page":"1424","volume":"9","author":"A Ker","year":"2014","unstructured":"A. Ker, T. Pevn\u00fd, The steganographer is the outlier: realistic large-scale steganalysis. TIFS 9(9), 1424\u20131435 (2014)","journal-title":"TIFS"},{"key":"171_CR54","doi-asserted-by":"crossref","unstructured":"M.\u00a0Kharrazi, H.\u00a0Sencar, N.\u00a0Memon, in SSWMC, Benchmarking steganographic and steganalysis techniques, vol. 5681 (SPIE, 2005), pp. 252\u2013263","DOI":"10.1117\/12.587375"},{"key":"171_CR55","doi-asserted-by":"crossref","unstructured":"M.\u00a0Kharrazi, H.\u00a0Sencar, N.\u00a0Memon, Performance study of common image steganography and steganalysis techniques. EI 15(4), 041104 (2006)","DOI":"10.1117\/1.2400672"},{"key":"171_CR56","doi-asserted-by":"crossref","unstructured":"J.\u00a0Kodovsk\u00fd, V.\u00a0Sedighi, J.\u00a0Fridrich, in MWSF, Study of cover source mismatch in steganalysis and ways to mitigate its impact, vol. 9028 (SPIE, 2014), pp. 204\u2013215","DOI":"10.1117\/12.2039693"},{"key":"171_CR57","doi-asserted-by":"publisher","first-page":"458","DOI":"10.1016\/j.neucom.2016.06.037","volume":"214","author":"X Kong","year":"2016","unstructured":"X. Kong, C. Feng, M. Li, Y. Guo, Iterative multi-order feature alignment for JPEG mismatched steganalysis. Neurocomputing 214, 458\u2013470 (2016)","journal-title":"Neurocomputing"},{"key":"171_CR58","doi-asserted-by":"crossref","unstructured":"V.\u00a0Lachner, K.\u00a0Schaar, R.\u00a0Zimmermann, in ICASSP, CSM in motion vector steganalysis: the effect of coders on motion vectors in H.264 video encoding (IEEE, 2023), pp. 1\u20135","DOI":"10.1109\/ICASSP49357.2023.10096323"},{"key":"171_CR59","doi-asserted-by":"crossref","unstructured":"V.\u00a0Leask, R.\u00a0Cogranne, D.\u00a0Borghys, H.\u00a0Bruyninckx, in ARES, UNCOVER: development of an efficient steganalysis framework for uncovering hidden data in digital media (ACM, 2022), pp. 1\u20138","DOI":"10.1145\/3538969.3544468"},{"key":"171_CR60","unstructured":"D.\u00a0Lerch\u00a0Hostalot, D.\u00a0Meg\u00edas\u00a0Jim\u00e9nez, Diagn\u00f3stico de CSM en Estegoan\u00e1lisis (RECSI, 2018)"},{"key":"171_CR61","doi-asserted-by":"crossref","unstructured":"D.\u00a0Lerch-Hostalot, D.\u00a0Megias, in ARES, Real-world actor-based image steganalysis via classifier inconsistency detection (ACM, 2023)","DOI":"10.1145\/3600160.3605042"},{"key":"171_CR62","doi-asserted-by":"publisher","unstructured":"D.\u00a0Lerch-Hostalot, D.\u00a0Meg\u00edas, in IH&MMSec, Detection of classifier inconsistencies in image steganalysis,\u00a0Proceedings of the ACM Workshop on Information Hiding and Multimedia Security (Association for Computing Machinery,\u00a0New York, 2019), pp. 222\u2013229. https:\/\/doi.org\/10.1145\/3335203.3335738","DOI":"10.1145\/3335203.3335738"},{"key":"171_CR63","unstructured":"D.\u00a0Lerch-Hostalot, D, Manifold alignment approach to cover source mismatch in steganalysis,\u00a0XIVth Reuni\u00f3n Espa\u00f1ola de Criptograf\u00eda y Seguridad (RESCI), RESCI (Mah\u00f3n, 2016)"},{"key":"171_CR64","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1016\/j.engappai.2015.12.013","volume":"50","author":"D Lerch-Hostalot","year":"2016","unstructured":"D. Lerch-Hostalot, D. Meg\u00edas, Unsupervised steganalysis based on artificial training sets. Eng. Appl. Artif. Intell. 50, 45\u201359 (2016)","journal-title":"Eng. Appl. Artif. Intell."},{"key":"171_CR65","doi-asserted-by":"crossref","unstructured":"X.\u00a0Li, X.\u00a0Kong, B.\u00a0Wang, Y.\u00a0Guo, X.\u00a0You, in ICIP, Generalized transfer component analysis for mismatched JPEG steganalysis (IEEE, 2013), pp. 4432\u20134436","DOI":"10.1109\/ICIP.2013.6738913"},{"issue":"7","key":"171_CR66","first-page":"319","volume":"2018","author":"L Lin","year":"2018","unstructured":"L. Lin, J. Newman, S. Reinders, Y. Guan, M. Wu, Domain adaptation in steganalysis for the spatial domain. MWSF 2018(7), 319\u20131 (2018)","journal-title":"MWSF"},{"key":"171_CR67","first-page":"1475","volume":"28","author":"Y Lin","year":"2020","unstructured":"Y. Lin, R. Wang, L. Dong, D. Yan, J. Wang, Tackling the cover-source mismatch problem in audio steganalysis with unsupervised domain adaptation. SPL 28, 1475\u20131479 (2020)","journal-title":"SPL"},{"key":"171_CR68","doi-asserted-by":"crossref","unstructured":"C.\u00a0Liu, M.\u00a0Kirchner, in IH&MMSec, CNN-based rescaling factor estimation (ACM, 2019), pp. 119\u2013124","DOI":"10.1145\/3335203.3335725"},{"key":"171_CR69","doi-asserted-by":"crossref","unstructured":"I.\u00a0Lubenko, A.\u00a0Ker, in MMSec, Steganalysis with mismatched covers: do simple classifiers help? (ACM, 2012), pp. 11\u201318","DOI":"10.1145\/2361407.2361410"},{"key":"171_CR70","doi-asserted-by":"crossref","unstructured":"I.\u00a0Lubenko, A.\u00a0Ker, in MWSF, Going from small to large data in steganalysis, vol. 8303 (SPIE, 2012), pp. 172\u2013181","DOI":"10.1117\/12.910214"},{"key":"171_CR71","doi-asserted-by":"crossref","unstructured":"I.\u00a0Lubenko, A.\u00a0Ker, in MWSF, Steganalysis using logistic regression, vol. 7880 (SPIE, 2011), pp. 193\u2013203","DOI":"10.1117\/12.872245"},{"key":"171_CR72","doi-asserted-by":"publisher","first-page":"1075","DOI":"10.1007\/s40264-017-0558-6","volume":"40","author":"Y Luo","year":"2017","unstructured":"Y. Luo, W. Thompson, T. Herr, Z. Zeng, M. Berendsen, S. Jonnalagadda, M. Carson, J. Starren, Natural language processing for EHR-based pharmacovigilance: a structured review. Drug Saf. 40, 1075\u20131089 (2017)","journal-title":"Drug Saf."},{"key":"171_CR73","doi-asserted-by":"crossref","unstructured":"S.\u00a0Lyu, H.\u00a0Farid, in SSWMC, Steganalysis using color wavelet statistics and one-class support vector machines, vol. 5306 (SPIE, 2004), pp. 35\u201345","DOI":"10.1117\/12.526012"},{"key":"171_CR74","doi-asserted-by":"crossref","unstructured":"J.\u00a0Makelberge, A.\u00a0Ker, in MWSF, Exploring multitask learning for steganalysis, vol. 8665 (SPIE, 2013), pp. 218\u2013227","DOI":"10.1117\/12.2004261"},{"key":"171_CR75","unstructured":"A.\u00a0Mallet, R.\u00a0Cogranne, P.\u00a0Bas, Q.\u00a0Giboulot, in XXIX\u00e8me Colloque Francophone de Traitement du Signal et des Images, Identification de D\u00e9veloppements d\u2019Images par Matrices de Corr\u00e9lations (Universit\u00e9 de Grenoble and Association Gretsi, 2023), GRETSI\u201923"},{"key":"171_CR76","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1016\/j.ins.2014.05.028","volume":"281","author":"W Ng","year":"2014","unstructured":"W. Ng, Z.M. He, D. Yeung, P. Chan, Steganalysis classifier training via minimizing sensitivity for different imaging sources. Inf. Sci. 281, 211\u2013224 (2014)","journal-title":"Inf. Sci."},{"issue":"10","key":"171_CR77","first-page":"4661","volume":"56","author":"T Nguyen","year":"2008","unstructured":"T. Nguyen, S. Oraintara, The shiftable complex directional pyramid-part II: implementation and applications. TSP 56(10), 4661\u20134672 (2008)","journal-title":"TSP"},{"key":"171_CR78","unstructured":"J.\u00a0Pasquet, S.\u00a0Bringay, M.\u00a0Chaumont, in EUSIPCO, Steganalysis with cover-source mismatch and a small learning database (IEEE, 2014), pp. 2425\u20132429"},{"key":"171_CR79","doi-asserted-by":"crossref","unstructured":"X.\u00a0Peng, Q.\u00a0Bai, X.\u00a0Xia, Z.\u00a0Huang, K.\u00a0Saenko, B.\u00a0Wang, in ICCV, Moment matching for multi-source domain adaptation (IEEE, 2019), pp. 1406\u20131415","DOI":"10.1109\/ICCV.2019.00149"},{"key":"171_CR80","doi-asserted-by":"crossref","unstructured":"T.\u00a0Pevn\u00fd, in MWSF, Detecting messages of unknown length, vol. 7880 (SPIE, 2011), pp. 300\u2013311","DOI":"10.1117\/12.872528"},{"key":"171_CR81","unstructured":"T.\u00a0Pevn\u00fd, Kernel Methods in Steganalysis (SUNY Binghamton, 2008)"},{"key":"171_CR82","doi-asserted-by":"crossref","unstructured":"T.\u00a0Pevn\u00fd, J.\u00a0Fridrich, in IWDW, Towards multi-class blind steganalyzer for JPEG images (Springer, 2005), pp. 39\u201353","DOI":"10.1007\/11551492_4"},{"key":"171_CR83","doi-asserted-by":"crossref","unstructured":"T.\u00a0Pevn\u00fd, J.\u00a0Fridrich, in SSWMC, Merging Markov and DCT features for multi-class JPEG steganalysis, vol. 6505 (SPIE, 2007), pp. 28\u201340","DOI":"10.1117\/12.696774"},{"key":"171_CR84","doi-asserted-by":"crossref","unstructured":"T.\u00a0Pevn\u00fd, A.\u00a0Ker, in MWSF, The challenges of rich features in universal steganalysis, vol. 8665 (SPIE, 2013), pp. 203\u2013217","DOI":"10.1117\/12.2006790"},{"key":"171_CR85","doi-asserted-by":"crossref","unstructured":"T.\u00a0Pevn\u00fd, I.\u00a0Nikolaev, in WIFS, Optimizing pooling function for pooled steganalysis (IEEE, 2015), pp. 1\u20136","DOI":"10.1109\/WIFS.2015.7368555"},{"issue":"4","key":"171_CR86","first-page":"635","volume":"3","author":"T Pevn\u00fd","year":"2008","unstructured":"T. Pevn\u00fd, J. Fridrich, Multiclass detector of current steganographic methods for JPEG format. TIFS 3(4), 635\u2013650 (2008)","journal-title":"TIFS"},{"issue":"3","key":"171_CR87","first-page":"505","volume":"9","author":"A Polesel","year":"2000","unstructured":"A. Polesel, G. Ramponi, V.J. Mathews, Image enhancement via adaptive unsharp masking. TIP 9(3), 505\u2013510 (2000)","journal-title":"TIP"},{"issue":"1","key":"171_CR88","doi-asserted-by":"publisher","first-page":"34","DOI":"10.1109\/MSP.2005.1407713","volume":"22","author":"R Ramanath","year":"2005","unstructured":"R. Ramanath, W. Snyder, Y. Yoo, M. Drew, Color image processing pipeline. Signal Proc. Mag. 22(1), 34\u201343 (2005)","journal-title":"Signal Proc. Mag."},{"key":"171_CR89","doi-asserted-by":"crossref","unstructured":"A.\u00a0Ramponi, B.\u00a0Plank, in ICCL, Neural unsupervised domain adaptation in NLP \u2013 survey (ACL, 2020), pp. 6838\u20136855","DOI":"10.18653\/v1\/2020.coling-main.603"},{"key":"171_CR90","doi-asserted-by":"crossref","first-page":"1","DOI":"10.2352\/ISSN.2470-1173.2019.5.MWSF-535","volume":"31","author":"S Reinders","year":"2019","unstructured":"S. Reinders, L. Lin, Y. Guan, M. Wu, J. Newman, Algorithm mismatch in spatial steganalysis. EI 31, 1\u201311 (2019)","journal-title":"EI"},{"key":"171_CR91","doi-asserted-by":"publisher","first-page":"68970","DOI":"10.1109\/ACCESS.2019.2918086","volume":"7","author":"TS Reinel","year":"2019","unstructured":"T.S. Reinel, R.P. Raul, I. Gustavo, Deep learning applied to steganalysis of digital images: a systematic review. IEEE Access 7, 68970\u201368990 (2019)","journal-title":"IEEE Access"},{"key":"171_CR92","doi-asserted-by":"crossref","unstructured":"E.\u00a0Rodr\u00edguez-Lois, D.\u00a0V\u00e1zquez-Pad\u00edn, F.\u00a0P\u00e9rez-Gonz\u00e1lez, P.\u00a0Comesana-Alfaro, in EUSIPCO, A critical look into quantization table generalization capabilities of CNN-based double JPEG compression detection (IEEE, 2022), pp. 1022\u20131026","DOI":"10.23919\/EUSIPCO55093.2022.9909784"},{"issue":"10","key":"171_CR93","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3560260","volume":"55","author":"A Rogers","year":"2023","unstructured":"A. Rogers, M. Gardner, I. Augenstein, QA dataset explosion: a taxonomy of NLP resources for question answering and reading comprehension. ACM Comput. Surv. 55(10), 1\u201345 (2023)","journal-title":"ACM Comput. Surv."},{"key":"171_CR94","unstructured":"D.\u00a0\u0160ep\u00e1k, L.\u00a0Adam, T.\u00a0Pevn\u00fd, in EUSIPCO, Formalizing cover-source mismatch as a robust optimization (IEEE, 2022)"},{"key":"171_CR95","doi-asserted-by":"crossref","unstructured":"H.\u00a0Shi, J.\u00a0Dong, W.\u00a0Wang, Y.\u00a0Qian, X.\u00a0Zhang, in PCM, SSGAN: secure steganography based on generative adversarial networks (Springer, 2018), pp. 534\u2013544","DOI":"10.1007\/978-3-319-77380-3_51"},{"key":"171_CR96","doi-asserted-by":"publisher","unstructured":"X.\u00a0Song, F.\u00a0Liu, C.\u00a0Yang, X.\u00a0Luo, Y.\u00a0Zhang, in IH &MMSec, Steganalysis of adaptive JPEG steganography using 2D Gabor filters (Association for Computing Machinery,\u00a0New York, 2015), pp. 15\u201323.\u00a0https:\/\/doi.org\/10.1145\/2756601.2756608","DOI":"10.1145\/2756601.2756608"},{"key":"171_CR97","doi-asserted-by":"publisher","first-page":"263","DOI":"10.1016\/j.sigpro.2013.11.027","volume":"98","author":"TH Thai","year":"2014","unstructured":"T.H. Thai, F. Retraint, R. Cogranne, Statistical detection of data hidden in least significant bits of clipped images. Sig. Process 98, 263\u2013274 (2014)","journal-title":"Sig. Process"},{"key":"171_CR98","doi-asserted-by":"crossref","unstructured":"X.\u00a0Xu, J.\u00a0Dong, W.\u00a0Wang, T.\u00a0Tan, in ICIP, Robust steganalysis based on training set construction and ensemble classifiers weighting (IEEE, 2015), pp. 1498\u20131502","DOI":"10.1109\/ICIP.2015.7351050"},{"key":"171_CR99","first-page":"8151","volume":"78","author":"Y Xue","year":"2019","unstructured":"Y. Xue, L. Yang, J. Wen, S. Niu, P. Zhong, A subspace learning-based method for JPEG mismatched steganalysis. MTAP 78, 8151\u20138166 (2019)","journal-title":"MTAP"},{"key":"171_CR100","first-page":"17993","volume":"77","author":"Y Yang","year":"2018","unstructured":"Y. Yang, X. Kong, C. Feng, Double-compressed JPEG images steganalysis with transferring feature. MTAP 77, 17993\u201318005 (2018)","journal-title":"MTAP"},{"key":"171_CR101","first-page":"116052","volume":"90","author":"L Yang","year":"2021","unstructured":"L. Yang, M. Men, Y. Xue, J. Wen, P. Zhong, Transfer subspace learning based on structure preservation for JPEG image mismatched steganalysis. SPIC 90, 116052 (2021)","journal-title":"SPIC"},{"issue":"4","key":"171_CR102","doi-asserted-by":"publisher","first-page":"2871","DOI":"10.1007\/s10462-022-10230-4","volume":"56","author":"S Yao","year":"2023","unstructured":"S. Yao, Q. Kang, M. Zhou, M. Rawa, A. Abusorrah, A survey of transfer learning for machinery diagnostics and prognostics. Artif. Intell. Rev. 56(4), 2871\u20132922 (2023)","journal-title":"Artif. Intell. Rev."},{"key":"171_CR103","doi-asserted-by":"publisher","unstructured":"Y.\u00a0Yousfi, J.\u00a0Butora, J.\u00a0Fridrich, C.\u00a0Fuji\u00a0Tsang, in IH&MMSec, Improving EfficientNet for JPEG steganalysis,\u00a0Proceedings of the 2021 ACM Workshop on Information Hiding and Multimedia Security. (Association for Computing Machinery,\u00a0New York, 2021), pp. 149\u2013157.\u00a0https:\/\/doi.org\/10.1145\/3437880.3460397","DOI":"10.1145\/3437880.3460397"},{"key":"171_CR104","doi-asserted-by":"crossref","unstructured":"Y.\u00a0Yousfi, J.\u00a0Fridrich, JPEG steganalysis detectors scalable with respect to compression quality. EI 32, 1\u201311 (2020)","DOI":"10.2352\/ISSN.2470-1173.2020.4.MWSF-075"},{"key":"171_CR105","doi-asserted-by":"publisher","unstructured":"L.\u00a0Yu, S.\u00a0Weng, M.\u00a0Chen, Y.\u00a0Wei, RCDD: contrastive domain discrepancy with reliable steganalysis labeling for cover source mismatch. Expert Syst. Appl. 237, 121543 (2024).\u00a0https:\/\/doi.org\/10.1016\/j.eswa.2023.121543","DOI":"10.1016\/j.eswa.2023.121543"},{"key":"171_CR106","doi-asserted-by":"crossref","unstructured":"L.\u00a0Zeng, X.\u00a0Kong, M.\u00a0Li, Y.\u00a0Guo, in MWSF, JPEG quantization table mismatched steganalysis via robust discriminative feature transformation, vol. 9409 (SPIE, 2015), pp. 270\u2013278","DOI":"10.1117\/12.2078188"},{"key":"171_CR107","doi-asserted-by":"crossref","unstructured":"X.\u00a0Zhang, X.\u00a0Kong, P.\u00a0Wang, B.\u00a0Wang, in WDW, Cover-source mismatch in deep spatial steganalysis (Springer, 2019), pp. 71\u201383","DOI":"10.1007\/978-3-030-43575-2_6"},{"key":"171_CR108","doi-asserted-by":"crossref","unstructured":"L.\u00a0Zhang, H.\u00a0Wang, P.\u00a0He, S.M. Abdullahi, B.\u00a0Li, Feature-guided deep subdomain adaptation network for dataset mismatch in spatial steganalysis (2021)","DOI":"10.21203\/rs.3.rs-1126251\/v1"},{"issue":"5","key":"171_CR109","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3178115","volume":"9","author":"Z Zhang","year":"2018","unstructured":"Z. Zhang, J. Geiger, J. Pohjalainen, A.E.D. Mousa, W. Jin, B. Schuller, Deep learning for environmentally robust speech recognition: an overview of recent developments. TIST 9(5), 1\u201328 (2018)","journal-title":"TIST"},{"key":"171_CR110","doi-asserted-by":"publisher","unstructured":"L. Zhang, S. Abdullahi, P. He, H. Wang, Dataset mismatched steganalysis using subdomain adaptation with guiding feature. Telecommun. Syst. Kluwer Academic Publishers,\u00a0USA,\u00a080(2), 263\u2013276 (2022).\u00a0https:\/\/doi.org\/10.1007\/s11235-022-00901-6","DOI":"10.1007\/s11235-022-00901-6"},{"key":"171_CR111","doi-asserted-by":"crossref","unstructured":"W.\u00a0Zhao, J.P. Queralta, T.\u00a0Westerlund, in SSCI, Sim-to-real transfer in deep reinforcement learning for robotics: a survey (IEEE, 2020), pp. 737\u2013744","DOI":"10.1109\/SSCI47803.2020.9308468"},{"issue":"2","key":"171_CR112","first-page":"183","volume":"40","author":"L Zhou","year":"2007","unstructured":"L. Zhou, G. Hripcsak, Temporal reasoning with medical data - a review with emphasis on medical natural language processing. JBI 40(2), 183\u2013202 (2007)","journal-title":"JBI"},{"issue":"5","key":"171_CR113","doi-asserted-by":"publisher","first-page":"820","DOI":"10.1109\/JPROC.2021.3054390","volume":"109","author":"SK Zhou","year":"2021","unstructured":"S.K. Zhou, H. Greenspan, C. Davatzikos, J. Duncan, B. Van Ginneken, A. Madabhushi, J. Prince, D. Rueckert, R. Summers, A review of deep learning in medical imaging: imaging traits, technology trends, case studies with progress highlights, and future promises. Proc. IEEE. 109(5), 820\u2013838 (2021)","journal-title":"Proc. IEEE."}],"container-title":["EURASIP Journal on Information Security"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13635-024-00171-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s13635-024-00171-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13635-024-00171-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,26]],"date-time":"2024-11-26T11:17:32Z","timestamp":1732619852000},"score":1,"resource":{"primary":{"URL":"https:\/\/jis-eurasipjournals.springeropen.com\/articles\/10.1186\/s13635-024-00171-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8,12]]},"references-count":113,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2024,12]]}},"alternative-id":["171"],"URL":"https:\/\/doi.org\/10.1186\/s13635-024-00171-6","relation":{"has-preprint":[{"id-type":"doi","id":"10.21203\/rs.3.rs-3812991\/v1","asserted-by":"object"}]},"ISSN":["2510-523X"],"issn-type":[{"value":"2510-523X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,8,12]]},"assertion":[{"value":"3 January 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 June 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 August 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"26"}}