{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T08:37:02Z","timestamp":1774600622834,"version":"3.50.1"},"reference-count":119,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2020,3,4]],"date-time":"2020-03-04T00:00:00Z","timestamp":1583280000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development of China","doi-asserted-by":"publisher","award":["2016YFB0800404"],"award-info":[{"award-number":["2016YFB0800404"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61672090, 61532005, 61332012"],"award-info":[{"award-number":["61672090, 61532005, 61332012"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["2018JBZ001, 2017YJS054"],"award-info":[{"award-number":["2018JBZ001, 2017YJS054"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Imaging"],"abstract":"<jats:p>Image source forensics is widely considered as one of the most effective ways to verify in a blind way digital image authenticity and integrity. In the last few years, many researchers have applied data-driven approaches to this task, inspired by the excellent performance obtained by those techniques on computer vision problems. In this survey, we present the most important data-driven algorithms that deal with the problem of image source forensics. To make order in this vast field, we have divided the area in five sub-topics: source camera identification, recaptured image forensic, computer graphics (CG) image forensic, GAN-generated image detection, and source social network identification. Moreover, we have included the works on anti-forensics and counter anti-forensics. For each of these tasks, we have highlighted advantages and limitations of the methods currently proposed in this promising and rich research field.<\/jats:p>","DOI":"10.3390\/jimaging6030009","type":"journal-article","created":{"date-parts":[[2020,3,6]],"date-time":"2020-03-06T07:33:46Z","timestamp":1583480026000},"page":"9","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":71,"title":["A Survey of Deep Learning-Based Source Image Forensics"],"prefix":"10.3390","volume":"6","author":[{"given":"Pengpeng","family":"Yang","sequence":"first","affiliation":[{"name":"Institute of Information Science, Beijing Jiaotong University, Beijing 100044, China"},{"name":"Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing Jiaotong University, Beijing 100044, China"}]},{"given":"Daniele","family":"Baracchi","sequence":"additional","affiliation":[{"name":"Department of Information Engineering, University of Florence, Via di S. Marta, 3, 50139 Florence, Italy"}]},{"given":"Rongrong","family":"Ni","sequence":"additional","affiliation":[{"name":"Institute of Information Science, Beijing Jiaotong University, Beijing 100044, China"},{"name":"Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing Jiaotong University, Beijing 100044, China"}]},{"given":"Yao","family":"Zhao","sequence":"additional","affiliation":[{"name":"Institute of Information Science, Beijing Jiaotong University, Beijing 100044, China"},{"name":"Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing Jiaotong University, Beijing 100044, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7776-4015","authenticated-orcid":false,"given":"Fabrizio","family":"Argenti","sequence":"additional","affiliation":[{"name":"Department of Information Engineering, University of Florence, Via di S. Marta, 3, 50139 Florence, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3047-0519","authenticated-orcid":false,"given":"Alessandro","family":"Piva","sequence":"additional","affiliation":[{"name":"Department of Information Engineering, University of Florence, Via di S. Marta, 3, 50139 Florence, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2020,3,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1109\/MSP.2004.1276112","article-title":"When seeing isn\u2019t believing [multimedia authentication technologies]","volume":"21","author":"Zhu","year":"2004","journal-title":"IEEE Signal Process. 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