{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T02:37:14Z","timestamp":1760150234350,"version":"build-2065373602"},"reference-count":49,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2023,11,3]],"date-time":"2023-11-03T00:00:00Z","timestamp":1698969600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"King Saud University, Saudi Arabia","award":["RSP2023R503"],"award-info":[{"award-number":["RSP2023R503"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Color face images are often transmitted over public channels, where they are vulnerable to tampering attacks. To address this problem, the present paper introduces a novel scheme called Authentication and Color Face Self-Recovery (AuCFSR) for ensuring the authenticity of color face images and recovering the tampered areas in these images. AuCFSR uses a new two-dimensional hyperchaotic system called two-dimensional modular sine-cosine map (2D MSCM) to embed authentication and recovery data into the least significant bits of color image pixels. This produces high-quality output images with high security level. When tampered color face image is detected, AuCFSR executes two deep learning models: the CodeFormer model to enhance the visual quality of the recovered color face image and the DeOldify model to improve the colorization of this image. Experimental results demonstrate that AuCFSR outperforms recent similar schemes in tamper detection accuracy, security level, and visual quality of the recovered images.<\/jats:p>","DOI":"10.3390\/s23218957","type":"journal-article","created":{"date-parts":[[2023,11,3]],"date-time":"2023-11-03T10:59:54Z","timestamp":1699009194000},"page":"8957","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["AuCFSR: Authentication and Color Face Self-Recovery Using Novel 2D Hyperchaotic System and Deep Learning Models"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2326-9550","authenticated-orcid":false,"given":"Achraf","family":"Daoui","sequence":"first","affiliation":[{"name":"National School of Applied Sciences, Sidi Mohamed Ben Abdellah University, Fez 30000, Morocco"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9436-8361","authenticated-orcid":false,"given":"Mohamed","family":"Yamni","sequence":"additional","affiliation":[{"name":"Dhar El Mahrez Faculty of Science, Sidi Mohamed Ben Abdellah University, Fez 30000, Morocco"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Torki","family":"Altameem","sequence":"additional","affiliation":[{"name":"Computer Science Department, Community College, King Saud University, Riyadh 11451, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4915-9325","authenticated-orcid":false,"given":"Musheer","family":"Ahmad","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering, Jamia Millia Islamia, New Delhi 110025, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6506-3083","authenticated-orcid":false,"given":"Mohamed","family":"Hammad","sequence":"additional","affiliation":[{"name":"Department of Information Technology, Faculty of Computers and Information, Menoufia University, Shibin El Kom 32511, Egypt"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4317-2801","authenticated-orcid":false,"given":"Pawe\u0142","family":"P\u0142awiak","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Faculty of Computer Science and Telecommunications, Cracow University of Technology, Warszawska 24, 31-155 Krakow, Poland"},{"name":"Institute of Theoretical and Applied Informatics, Polish Academy of Sciences, Ba\u0142tycka 5, 44-100 Gliwice, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9675-5819","authenticated-orcid":false,"given":"Ryszard","family":"Tadeusiewicz","sequence":"additional","affiliation":[{"name":"Department of Biocybernetics and Biomedical Engineering, AGH University of Science and Technology, 30-059 Krakow, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5068-2033","authenticated-orcid":false,"given":"Ahmed","family":"A. Abd El-Latif","sequence":"additional","affiliation":[{"name":"Information Countermeauser Technique Institute, School of Cyberspace Science, Faculty of Computing, Harbin Institute of Technology, Harbin 150001, China"},{"name":"Department of Mathematics and Computer Science, Faculty of Science, Menoufia University, Shibin El Kom 32511, Egypt"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,11,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1007\/s13735-020-00197-9","article-title":"Recent Trends in Image Watermarking Techniques for Copyright Protection: A Survey","volume":"9","author":"Ray","year":"2020","journal-title":"Int. J. Multimed. Inf. Retr."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Rathgeb, C., Tolosana, R., Vera-Rodriguez, R., and Busch, C. (2022). Handbook of Digital Face Manipulation and Detection: From DeepFakes to Morphing Attacks, Springer International Publishing. Advances in Computer Vision and Pattern Recognition.","DOI":"10.1007\/978-3-030-87664-7"},{"key":"ref_3","first-page":"5822","article-title":"AuSR1: Authentication and Self-Recovery Using a New Image Inpainting Technique with LSB Shifting in Fragile Image Watermarking","volume":"34","author":"Aminuddin","year":"2022","journal-title":"J. King Saud Univ.-Comput. Inf. Sci."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"108207","DOI":"10.1016\/j.compeleceng.2022.108207","article-title":"AuSR2: Image Watermarking Technique for Authentication and Self-Recovery with Image Texture Preservation","volume":"102","author":"Aminuddin","year":"2022","journal-title":"Comput. Electr. Eng."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"29805","DOI":"10.1007\/s11042-021-11179-2","article-title":"A Dual-Tamper-Detection Method for Digital Image Authentication and Content Self-Recovery","volume":"80","author":"Liu","year":"2021","journal-title":"Multimed. Tools Appl."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"631","DOI":"10.1109\/TLA.2020.9082736","article-title":"Watermarking Framework for Authentication and Self-Recovery of Tampered Colour Images","volume":"18","author":"Molina","year":"2020","journal-title":"IEEE Lat. Am. Trans."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Faheem, Z.B., Ali, M., Raza, M.A., Arslan, F., Ali, J., Masud, M., and Shorfuzzaman, M. (2022). Image Watermarking Scheme Using LSB and Image Gradient. Appl. Sci., 12.","DOI":"10.3390\/app12094202"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"115725","DOI":"10.1016\/j.image.2019.115725","article-title":"An Effective Fragile Watermarking Scheme for Color Image Tampering Detection and Self-Recovery","volume":"81","author":"Ponomaryov","year":"2020","journal-title":"Signal Process. Image Commun."},{"key":"ref_9","unstructured":"Agrawal, A., Tripathi, R.C., Do, E.Y.-L., and Tiwari, M.D. Self-Embedding Pixel Wise Fragile Watermarking Scheme for Image Authentication. Proceedings of the Intelligent Interactive Technologies and Multimedia."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"5108","DOI":"10.1109\/TII.2020.3028612","article-title":"DWFCAT: Dual Watermarking Framework for Industrial Image Authentication and Tamper Localization","volume":"17","author":"Kamili","year":"2021","journal-title":"IEEE Trans. Ind. Inform."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"3497","DOI":"10.1016\/j.patcog.2008.05.003","article-title":"Dual Watermark for Image Tamper Detection and Recovery","volume":"41","author":"Lee","year":"2008","journal-title":"Pattern Recognit."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1784","DOI":"10.1109\/TIP.2020.3048629","article-title":"Dynamic Selection Network for Image Inpainting","volume":"30","author":"Wang","year":"2021","journal-title":"IEEE Trans. Image Process."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2007","DOI":"10.1007\/s11063-019-10163-0","article-title":"Image Inpainting: A Review","volume":"51","author":"Elharrouss","year":"2020","journal-title":"Neural Process Lett."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"102028","DOI":"10.1016\/j.displa.2021.102028","article-title":"Image Inpainting Based on Deep Learning: A Review","volume":"69","author":"Qin","year":"2021","journal-title":"Displays"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"118070","DOI":"10.1016\/j.eswa.2022.118070","article-title":"ECNFP: Edge-Constrained Network Using a Feature Pyramid for Image Inpainting","volume":"207","author":"Wei","year":"2022","journal-title":"Expert. Syst. Appl."},{"key":"ref_16","first-page":"30599","article-title":"Towards Robust Blind Face Restoration with Codebook Lookup Transformer","volume":"35","author":"Zhou","year":"2022","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref_17","unstructured":"Jantic, J. (2023, September 16). Deoldify. GitHub: Github.com\/jantic\/DeOldify. Available online: https:\/\/github.com\/jantic\/DeOldify."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1016\/j.image.2012.12.003","article-title":"A Novel Chaos-Based Fragile Watermarking for Image Tampering Detection and Self-Recovery","volume":"28","author":"Tong","year":"2013","journal-title":"Signal Process. Image Commun."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"775","DOI":"10.1016\/j.jvcir.2016.04.023","article-title":"Effective Self-Embedding Watermarking Scheme for Image Tampered Detection and Localization with Recovery Capability","volume":"38","author":"Singh","year":"2016","journal-title":"J. Vis. Commun. Image Represent."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/j.displa.2017.01.001","article-title":"Hierarchical Recovery for Tampered Images Based on Watermark Self-Embedding","volume":"46","author":"Cao","year":"2017","journal-title":"Displays"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.image.2018.03.011","article-title":"Image Self-Recovery with Watermark Self-Embedding","volume":"65","author":"Tai","year":"2018","journal-title":"Signal Process. Image Commun."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1016\/j.image.2018.04.003","article-title":"An Enhanced Fragile Watermarking Scheme to Digital Image Protection and Self-Recovery","volume":"66","author":"Fan","year":"2018","journal-title":"Signal Process. Image Commun."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1016\/j.jvcir.2017.09.017","article-title":"TRLH: Fragile and Blind Dual Watermarking for Image Tamper Detection and Self-Recovery Based on Lifting Wavelet Transform and Halftoning Technique","volume":"50","author":"Taherinia","year":"2018","journal-title":"J. Vis. Commun. Image Represent."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Li, Y., Song, W., Zhao, X., Wang, J., and Zhao, L. (2019). A Novel Image Tamper Detection and Self-Recovery Algorithm Based on Watermarking and Chaotic System. Mathematics, 7.","DOI":"10.3390\/math7100955"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"169280","DOI":"10.1016\/j.ijleo.2022.169280","article-title":"Secure and Effective Color Image Tampering Detection and Self Restoration Using a Dual Watermarking Approach","volume":"262","author":"Ellubani","year":"2022","journal-title":"Optik"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"160840","DOI":"10.1109\/ACCESS.2020.3019832","article-title":"Effective Self-Recovery and Tampering Localization Fragile Watermarking for Medical Images","volume":"8","author":"Su","year":"2020","journal-title":"IEEE Access"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"169345","DOI":"10.1016\/j.ijleo.2022.169345","article-title":"Digital Image Self-Recovery Using CNN Networks","volume":"264","author":"Rezaei","year":"2022","journal-title":"Optik"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"166","DOI":"10.1007\/s00034-021-01764-z","article-title":"Efficient Methods for Signal Processing Using Charlier Moments and Artificial Bee Colony Algorithm","volume":"41","author":"Daoui","year":"2022","journal-title":"Circuits Syst. Signal Process."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"3007","DOI":"10.1109\/TCSVT.2017.2734838","article-title":"An End-to-End Compression Framework Based on Convolutional Neural Networks","volume":"28","author":"Jiang","year":"2017","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1016\/j.optlaseng.2019.04.011","article-title":"A Fast Image Encryption Algorithm Based on Compressive Sensing and Hyperchaotic Map","volume":"121","author":"Xu","year":"2019","journal-title":"Opt. Lasers Eng."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"107252","DOI":"10.1016\/j.optlastec.2021.107252","article-title":"Image Encryption Algorithm Based on 2D Hyperchaotic Map","volume":"142","author":"Gao","year":"2021","journal-title":"Opt. Laser Technol."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1016\/j.matcom.2017.10.002","article-title":"A New 4D Hyperchaotic System with High Complexity","volume":"146","author":"Chen","year":"2018","journal-title":"Math. Comput. Simul."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"380","DOI":"10.1016\/j.jvcir.2018.12.022","article-title":"A Survey on Image Tampering and Its Detection in Real-World Photos","volume":"58","author":"Zheng","year":"2019","journal-title":"J. Vis. Commun. Image Represent."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1841","DOI":"10.1109\/TIFS.2012.2218597","article-title":"An Evaluation of Popular Copy-Move Forgery Detection Approaches","volume":"7","author":"Christlein","year":"2012","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1016\/j.cag.2017.08.010","article-title":"Humans Are Easily Fooled by Digital Images","volume":"68","author":"Schetinger","year":"2017","journal-title":"Comput. Graph."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Yee, K., Tantipongpipat, U., and Mishra, S. (2021). Image Cropping on Twitter: Fairness Metrics, Their Limitations, and the Importance of Representation, Design, and Agency. Proc. ACM Hum.-Comput. Interact., 5.","DOI":"10.1145\/3479594"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Korshunova, I., Shi, W., Dambre, J., and Theis, L. (2017, January 22\u201329). Fast Face-Swap Using Convolutional Neural Networks. Proceedings of the 2017 IEEE International Conference on Computer Vision, Venice, Italy.","DOI":"10.1109\/ICCV.2017.397"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"103525","DOI":"10.1016\/j.cviu.2022.103525","article-title":"Deep Learning for Deepfakes Creation and Detection: A Survey","volume":"223","author":"Nguyen","year":"2022","journal-title":"Comput. Vis. Image Underst."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"727","DOI":"10.1109\/LSP.2007.896436","article-title":"Statistical Fragile Watermarking Capable of Locating Individual Tampered Pixels","volume":"14","author":"Zhang","year":"2007","journal-title":"IEEE Signal Process. Lett."},{"key":"ref_40","unstructured":"(2023, March 11). 70,000 Real Faces 2. Available online: https:\/\/www.kaggle.com\/datasets\/tunguz\/70000-real-faces-2."},{"key":"ref_41","unstructured":"Ekstrom, M.P. (2012). Digital Image Processing Techniques, Academic Press."},{"key":"ref_42","unstructured":"Zhou, S. (2023, September 16). Sczhou\/CodeFormer 2023. Available online: https:\/\/github.com\/sczhou\/CodeFormer."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Kim, C., and Yang, C.-N. (2021). Self-Embedding Fragile Watermarking Scheme to Detect Image Tampering Using AMBTC and OPAP Approaches. Appl. Sci., 11.","DOI":"10.3390\/app11031146"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"181893","DOI":"10.1109\/ACCESS.2020.3028315","article-title":"A Dynamic Three-Bit Image Steganography Algorithm for Medical and e-Healthcare Systems","volume":"8","author":"Siddiqui","year":"2020","journal-title":"IEEE Access"},{"key":"ref_45","unstructured":"(2023, April 28). FaceSwapper|Swap Photo Video Face Online Free. Available online: https:\/\/faceswapper.ai\/."},{"key":"ref_46","unstructured":"(2023, October 13). Flickr-Faces-HQ Dataset (FFHQ). Available online: https:\/\/www.kaggle.com\/datasets\/arnaud58\/flickrfaceshq-dataset-ffhq."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"144","DOI":"10.1109\/MCOM.2018.1700890","article-title":"Terahertz Technologies to Deliver Optical Network Quality of Experience in Wireless Systems Beyond 5G","volume":"56","author":"Boulogeorgos","year":"2018","journal-title":"IEEE Commun. Mag."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Daoui, A., Mao, H., Yamni, M., Li, Q., Alfarraj, O., and Abd El-Latif, A.A. (2023). Novel Integer Shmaliy Transform and New Multiparametric Piecewise Linear Chaotic Map for Joint Lossless Compression and Encryption of Medical Images in IoMTs. Mathematics, 11.","DOI":"10.3390\/math11163619"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"2129","DOI":"10.1142\/S0218127406015970","article-title":"Some Basic Cryptographic Requirements for Chaos-Based Cryptosystems","volume":"16","author":"Alvarez","year":"2006","journal-title":"Int. J. Bifurc. Chaos"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/21\/8957\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T21:16:38Z","timestamp":1760130998000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/21\/8957"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,11,3]]},"references-count":49,"journal-issue":{"issue":"21","published-online":{"date-parts":[[2023,11]]}},"alternative-id":["s23218957"],"URL":"https:\/\/doi.org\/10.3390\/s23218957","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2023,11,3]]}}}