{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T12:05:57Z","timestamp":1784203557927,"version":"3.55.0"},"reference-count":48,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["12271038"],"award-info":[{"award-number":["12271038"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005089","name":"Natural Science Foundation of Beijing Municipality","doi-asserted-by":"publisher","award":["L222018"],"award-info":[{"award-number":["L222018"]}],"id":[{"id":"10.13039\/501100005089","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012669","name":"Natural Science Foundation Project of Chongqing","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100012669","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004826","name":"Beijing Natural Science Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100004826","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005230","name":"Natural Science Foundation of Chongqing Municipality","doi-asserted-by":"publisher","award":["T01EF9C ECCXB016"],"award-info":[{"award-number":["T01EF9C ECCXB016"]}],"id":[{"id":"10.13039\/501100005230","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005230","name":"Natural Science Foundation of Chongqing Municipality","doi-asserted-by":"publisher","award":["CSTB2023NSCQMSX04 01"],"award-info":[{"award-number":["CSTB2023NSCQMSX04 01"]}],"id":[{"id":"10.13039\/501100005230","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004602","name":"Program for New Century Excellent Talents in University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100004602","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Neural Networks"],"published-print":{"date-parts":[[2026,10]]},"DOI":"10.1016\/j.neunet.2026.109089","type":"journal-article","created":{"date-parts":[[2026,5,10]],"date-time":"2026-05-10T05:45:58Z","timestamp":1778391958000},"page":"109089","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["A simultaneous dual watermarking scheme for deep learning models"],"prefix":"10.1016","volume":"202","author":[{"given":"Dehui","family":"Wang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9568-0392","authenticated-orcid":false,"given":"Yingqian","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuang","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2103-0052","authenticated-orcid":false,"given":"Yumei","family":"Xue","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.neunet.2026.109089_bib0001","series-title":"Proceedings of the twenty seventh usenix secur. symp.","first-page":"1615","article-title":"Turning your weakness into a strength: Watermarking deep learning models by backdooring","author":"Adi","year":"2018"},{"key":"10.1016\/j.neunet.2026.109089_bib0002","series-title":"Proc. the twenty seventh usenix secur. symp.","first-page":"1615","article-title":"Turning your weakness into a strength: Watermarking deep learning models by backdooring","author":"Adi","year":"2018"},{"issue":"2","key":"10.1016\/j.neunet.2026.109089_bib0003","doi-asserted-by":"crossref","first-page":"2261","DOI":"10.32604\/cmc.2023.038534","article-title":"Improved transportation model with internet of things using artificial intelligence algorithm","volume":"76","author":"Al-Ani","year":"2023","journal-title":"Computers, Materials & Continua"},{"issue":"12","key":"10.1016\/j.neunet.2026.109089_bib0004","first-page":"1","article-title":"Secure control of networked control systems using dynamic watermarking","volume":"52","author":"Du","year":"2021","journal-title":"IEEE Transactions on Cybernetics"},{"key":"10.1016\/j.neunet.2026.109089_bib0005","series-title":"Proc. neurips","first-page":"4714","article-title":"Rethinking deep neural network ownership verification: Embedding passports to defeat ambiguity attacks","author":"Fan","year":"2019"},{"issue":"2","key":"10.1016\/j.neunet.2026.109089_bib0006","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1111\/j.1469-1809.1936.tb02137.x","article-title":"The use of multiple measurements in taxonomic problems","volume":"7","author":"Fisher","year":"1936","journal-title":"Annals of Eugenics"},{"key":"10.1016\/j.neunet.2026.109089_bib0007","series-title":"Proc. Int. Conf. Comput. -Aided Des.","first-page":"1","article-title":"Watermarking deep learning models for embedded systems","author":"Guo","year":"2018"},{"key":"10.1016\/j.neunet.2026.109089_bib0008","series-title":"2016 IEEE conference on computer vision and pattern recognition","first-page":"770","article-title":"Deep residual learning for image recognition","author":"He","year":"2016"},{"key":"10.1016\/j.neunet.2026.109089_bib0009","unstructured":"Hitaj, D., & Mancini, L. (2018). Have you stolen my model? evasion attacks against deep neural network watermarking technique. arXiv preprint arXiv: 1809.00615."},{"issue":"8","key":"10.1016\/j.neunet.2026.109089_bib0010","doi-asserted-by":"crossref","first-page":"11204","DOI":"10.1109\/TNNLS.2023.3250210","article-title":"Unambiguous and high-fidelity backdoor watermarking for deep neural networks","volume":"35","author":"Hua","year":"2024","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"key":"10.1016\/j.neunet.2026.109089_bib0011","series-title":"2017 IEEE conference on computer vision and pattern recognition","first-page":"2261","article-title":"Densely connected convolutional networks","author":"Huang","year":"2017"},{"issue":"3","key":"10.1016\/j.neunet.2026.109089_bib0012","doi-asserted-by":"crossref","first-page":"999","DOI":"10.3390\/app11030999","article-title":"KeyNet: An asymmetric key-style framework for watermarking deep learning models","volume":"11","author":"Jebreel","year":"2021","journal-title":"Applied Sciences"},{"key":"10.1016\/j.neunet.2026.109089_bib0013","doi-asserted-by":"crossref","first-page":"641","DOI":"10.1038\/nmeth.4346","article-title":"Principal component analysis","volume":"14","author":"Lever","year":"2017","journal-title":"Nat Methods"},{"issue":"1","key":"10.1016\/j.neunet.2026.109089_bib0014","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1109\/MMUL.2024.3356494","article-title":"Cryptanalyzing an image encryption algorithm underpinned by 2-D lag-complex logistic map","volume":"31","author":"Li","year":"2024","journal-title":"IEEE MultiMedia"},{"key":"10.1016\/j.neunet.2026.109089_bib0015","series-title":"Proc. int. conf. acoust. speech signal.","first-page":"3049","article-title":"Fostering the robustness of white-box deep neural network watermarks by neuron alignment","volume":"Vol. 32","author":"Li","year":"2022"},{"key":"10.1016\/j.neunet.2026.109089_bib0016","doi-asserted-by":"crossref","first-page":"309","DOI":"10.3389\/fnins.2017.00309","article-title":"Cifar10-dvs: An event-stream dataset for object classification","volume":"11","author":"Li","year":"2017","journal-title":"Frontiers in Neuroscience"},{"key":"10.1016\/j.neunet.2026.109089_bib0017","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1109\/LSP.2023.3239737","article-title":"Universal blackmarks: Key-image-free blackbox multi-bit watermarking of deep neural networks","volume":"32","author":"Li","year":"2023","journal-title":"IEEE Signal Processing Letters"},{"key":"10.1016\/j.neunet.2026.109089_bib0018","doi-asserted-by":"crossref","DOI":"10.1016\/j.neunet.2024.106199","article-title":"SecureNet: Proactive intellectual property protection and model security defense for DNNs based on backdoor learning","volume":"174","author":"Li","year":"2024","journal-title":"Neural Networks"},{"issue":"23","key":"10.1016\/j.neunet.2026.109089_bib0019","doi-asserted-by":"crossref","first-page":"24373","DOI":"10.1109\/JIOT.2022.3188631","article-title":"Database watermarking algorithm based on decision tree shift correction","volume":"9","author":"Li","year":"2022","journal-title":"IEEE Internet of Things Journal"},{"key":"10.1016\/j.neunet.2026.109089_bib0020","doi-asserted-by":"crossref","first-page":"2318","DOI":"10.1109\/TIFS.2023.3265535","article-title":"Black-box dataset ownership verification via backdoor watermarking","volume":"18","author":"Li","year":"2023","journal-title":"IEEE Transactions on Information Forensics and Security"},{"key":"10.1016\/j.neunet.2026.109089_bib0021","series-title":"Proc. 35th annu. comput. secur. appl. conf.","first-page":"126","article-title":"How to prove your model belongs to you: A blind-watermark based framework to protect intellectual property of dnn","author":"Li","year":"2019"},{"issue":"6","key":"10.1016\/j.neunet.2026.109089_bib0022","doi-asserted-by":"crossref","first-page":"5766","DOI":"10.1109\/TDSC.2024.3384416","article-title":"Robust and imperceptible black-box dnn watermarking based on fourier perturbation analysis and frequency sensitivity clustering","volume":"21","author":"Liu","year":"2024","journal-title":"IEEE Transactions on Dependable and Secure Computing"},{"issue":"6","key":"10.1016\/j.neunet.2026.109089_bib0023","doi-asserted-by":"crossref","first-page":"5214","DOI":"10.1109\/TDSC.2023.3242737","article-title":"A robustness-assured white-box watermark in neural networks","volume":"20","author":"Lv","year":"2023","journal-title":"IEEE Transactions on Dependable and Secure Computing"},{"key":"10.1016\/j.neunet.2026.109089_bib0024","doi-asserted-by":"crossref","DOI":"10.1016\/j.neunet.2024.107077","article-title":"DFCL: Dual-pathway fusion contrastive learning for blind single-image visible watermark removal","volume":"184","author":"Meng","year":"2025","journal-title":"Neural Networks"},{"issue":"13","key":"10.1016\/j.neunet.2026.109089_bib0025","doi-asserted-by":"crossref","first-page":"9233","DOI":"10.1007\/s00521-019-04434-z","article-title":"Adversarial frontier stitching for remote neural network watermarking","volume":"32","author":"Merrer","year":"2020","journal-title":"Neural Computing and Applications"},{"issue":"1","key":"10.1016\/j.neunet.2026.109089_bib0026","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1007\/s13735-018-0147-1","article-title":"Digital watermarking for deep learning models","volume":"7","author":"Nagai","year":"2018","journal-title":"International Journal of Multimedia Information Retrieval"},{"key":"10.1016\/j.neunet.2026.109089_bib0027","series-title":"Proc. ACM Asia conf. comput. commun. secur.","first-page":"228","article-title":"Robust watermarking of neural network with exponential weighting","author":"Namba","year":"2019"},{"key":"10.1016\/j.neunet.2026.109089_bib0028","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1016\/j.neunet.2023.06.036","article-title":"The deep arbitrary polynomial chaos neural network or how deep artificial neural networks could benefit from data-driven homogeneous chaos theory","volume":"166","author":"Oladyshkin","year":"2023","journal-title":"Neural Networks"},{"key":"10.1016\/j.neunet.2026.109089_bib0029","doi-asserted-by":"crossref","DOI":"10.1016\/j.asoc.2025.112747","article-title":"Federated learning frameworks in smart e-Healthcare: a systematic literature review with bias evaluation","volume":"171","author":"Panda","year":"2025","journal-title":"Applied Soft Computing"},{"issue":"1","key":"10.1016\/j.neunet.2026.109089_bib0030","first-page":"1","article-title":"Internet of things (IoT) in smart cities: Enhancing urban living through technology","volume":"5","author":"Rehan","year":"2023","journal-title":"Journal of Engineering & Technology"},{"key":"10.1016\/j.neunet.2026.109089_bib0031","unstructured":"Rouhani, B., Chen, H., & Koushanfar, F. (2018). DeepSigns: A generic watermarking framework for ip protection of deep learning models. 10.48550\/arXiv.1804.00750."},{"key":"10.1016\/j.neunet.2026.109089_bib0032","doi-asserted-by":"crossref","DOI":"10.1016\/j.asoc.2024.111969","article-title":"Generation of black-box adversarial attacks using many independent objective-based algorithm for testing the robustness of deep neural networks","volume":"164","author":"Sahin","year":"2024","journal-title":"Applied Soft Computing"},{"key":"10.1016\/j.neunet.2026.109089_bib0033","article-title":"Pearson\u2019s correlation coefficient","volume":"345","author":"Sedgwick","year":"2012","journal-title":"BMJ"},{"key":"10.1016\/j.neunet.2026.109089_bib0034","series-title":"2023 Fifth international conference on electrical, computer and communication technologies","first-page":"1","article-title":"DenseNet201: A customized dnn model for multi-class classification and detection of tumors based on brain mri images","author":"Sujatha","year":"2023"},{"issue":"5","key":"10.1016\/j.neunet.2026.109089_bib0035","doi-asserted-by":"crossref","first-page":"7443","DOI":"10.1007\/s11042-022-13641-1","article-title":"ApaNet: Adversarial perturbations alleviation network for face verification","volume":"82","author":"Sun","year":"2023","journal-title":"Multimedia Tools and Applications"},{"key":"10.1016\/j.neunet.2026.109089_bib0036","doi-asserted-by":"crossref","DOI":"10.1016\/j.neunet.2024.106218","article-title":"A self-supervised network for image denoising and watermark removal","volume":"174","author":"Tian","year":"2024","journal-title":"Neural Networks"},{"key":"10.1016\/j.neunet.2026.109089_bib0037","series-title":"Proc. ACM int. conf. multimedia retr.","first-page":"269","article-title":"Embedding watermarks into deep learning models","author":"Uchida","year":"2017"},{"key":"10.1016\/j.neunet.2026.109089_bib0038","doi-asserted-by":"crossref","DOI":"10.1016\/j.neunet.2025.107473","article-title":"Multiscroll hidden attractor in memristive autapse neuron model and its memristor-based scroll control and application in image encryption","volume":"188","author":"Wan","year":"2025","journal-title":"Neural Networks"},{"key":"10.1016\/j.neunet.2026.109089_bib0039","doi-asserted-by":"crossref","first-page":"1","DOI":"10.2352\/ISSN.2470-1173.2020.4.MWSF-022","article-title":"Watermarking in deep learning models via error back-propagation","volume":"32","author":"Wang","year":"2020","journal-title":"Electronic Imaging"},{"issue":"11","key":"10.1016\/j.neunet.2026.109089_bib0040","first-page":"4251","article-title":"Feedback control-based parallel memristor-coupled sine map and its hardware implementation","volume":"70","author":"Wang","year":"2023","journal-title":"IEEE Transactions on Circuits and Systems II: Express Briefs"},{"issue":"3","key":"10.1016\/j.neunet.2026.109089_bib0041","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1016\/0167-2789(85)90011-9","article-title":"Determining Lyapunov exponents from a time series","volume":"16","author":"Wolf","year":"1985","journal-title":"Physica D"},{"issue":"14","key":"10.1016\/j.neunet.2026.109089_bib0042","first-page":"3320","article-title":"How transferable are features in deep learning models","volume":"2","author":"Yosinski","year":"2014","journal-title":"Advances in Neural Information Processing Systems"},{"key":"10.1016\/j.neunet.2026.109089_bib0043","series-title":"Proc. AsiaCCS","first-page":"159","article-title":"Marc pH Protecting intellectual property of deep learning models with watermarking","author":"Zhang","year":"2018"},{"issue":"23","key":"10.1016\/j.neunet.2026.109089_bib0044","doi-asserted-by":"crossref","first-page":"17120","DOI":"10.1109\/JIOT.2021.3078175","article-title":"An energy-efficient authentication scheme based on Chebyshev chaotic map for smart grid environments","volume":"8","author":"Zhang","year":"2021","journal-title":"IEEE Internet of Things Journal"},{"key":"10.1016\/j.neunet.2026.109089_bib0045","doi-asserted-by":"crossref","first-page":"54175","DOI":"10.1109\/ACCESS.2020.2979827","article-title":"An efficient image encryption scheme based on s-boxes and fractional-order differential logistic map","volume":"8","author":"Zhang","year":"2020","journal-title":"IEEE Access"},{"issue":"3","key":"10.1016\/j.neunet.2026.109089_bib0046","doi-asserted-by":"crossref","first-page":"19291","DOI":"10.1007\/s11042-021-10724-3","article-title":"A secure image encryption scheme based on genetic mutation and MLNCML chaotic system","volume":"80","author":"Zhang","year":"2021","journal-title":"Multimedia Tools and Applications"},{"key":"10.1016\/j.neunet.2026.109089_bib0047","doi-asserted-by":"crossref","first-page":"213296","DOI":"10.1109\/ACCESS.2020.3039323","article-title":"DeepTrigger: A watermarking scheme of deep learning models based on chaotic automatic data annotation","volume":"8","author":"Zhang","year":"2020","journal-title":"IEEE Access"},{"key":"10.1016\/j.neunet.2026.109089_bib0048","doi-asserted-by":"crossref","first-page":"2022","DOI":"10.1109\/TMM.2022.3142952","article-title":"Recognition-oriented image compressive sensing with deep learning","volume":"25","author":"Zhou","year":"2023","journal-title":"IEEE Transactions on Multimedia"}],"container-title":["Neural Networks"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0893608026005496?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0893608026005496?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T11:20:07Z","timestamp":1784200807000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0893608026005496"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,10]]},"references-count":48,"alternative-id":["S0893608026005496"],"URL":"https:\/\/doi.org\/10.1016\/j.neunet.2026.109089","relation":{},"ISSN":["0893-6080"],"issn-type":[{"value":"0893-6080","type":"print"}],"subject":[],"published":{"date-parts":[[2026,10]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"A simultaneous dual watermarking scheme for deep learning models","name":"articletitle","label":"Article Title"},{"value":"Neural Networks","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.neunet.2026.109089","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"109089"}}