{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T06:56:32Z","timestamp":1781679392402,"version":"3.54.5"},"reference-count":63,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Neurocomputing"],"published-print":{"date-parts":[[2026,9]]},"DOI":"10.1016\/j.neucom.2026.134024","type":"journal-article","created":{"date-parts":[[2026,5,19]],"date-time":"2026-05-19T15:17:18Z","timestamp":1779203838000},"page":"134024","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Boosting backdoor attack with a learnable poisoning sample selection strategy"],"prefix":"10.1016","volume":"695","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1225-1718","authenticated-orcid":false,"given":"Zihao","family":"Zhu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5322-0988","authenticated-orcid":false,"given":"Mingda","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-7021-5145","authenticated-orcid":false,"given":"Shaokui","family":"Wei","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Li","family":"Shen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yanbo","family":"Fan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Baoyuan","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.neucom.2026.134024_bib0005","doi-asserted-by":"crossref","first-page":"47230","DOI":"10.1109\/ACCESS.2019.2909068","article-title":"BadNets: evaluating backdooring attacks on deep neural networks","volume":"7","author":"Gu","year":"2019","journal-title":"IEEE Access"},{"key":"10.1016\/j.neucom.2026.134024_bib0010","author":"Chen"},{"key":"10.1016\/j.neucom.2026.134024_bib0015","series-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","article-title":"Invisible backdoor attack with sample-specific triggers","author":"Li","year":"2021"},{"key":"10.1016\/j.neucom.2026.134024_bib0020","series-title":"2019 IEEE International Conference on Image Processing","article-title":"A new backdoor attack in CNNS by training set corruption without label poisoning","author":"Barni","year":"2019"},{"key":"10.1016\/j.neucom.2026.134024_bib0025","series-title":"25th Annual Network and Distributed System Security Symposium","article-title":"Trojaning attack on neural networks","author":"Liu","year":"2018"},{"key":"10.1016\/j.neucom.2026.134024_bib0030","series-title":"International Conference on Machine Learning","article-title":"Understanding black-box predictions via influence functions","author":"Koh","year":"2017"},{"key":"10.1016\/j.neucom.2026.134024_bib0035","series-title":"International Conference on Machine Learning","article-title":"Not all samples are created equal: deep learning with importance sampling","author":"Katharopoulos","year":"2018"},{"key":"10.1016\/j.neucom.2026.134024_bib0040","first-page":"20596","article-title":"Deep learning on a data diet: finding important examples early in training","volume":"34","author":"Paul","year":"2021","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.neucom.2026.134024_bib0045","series-title":"International Conference on Learning Representations (ICLR)","article-title":"Selection via proxy: efficient data selection for deep learning","author":"Coleman","year":"2020"},{"key":"10.1016\/j.neucom.2026.134024_bib0050","author":"Toneva"},{"key":"10.1016\/j.neucom.2026.134024_bib0055","first-page":"14879","article-title":"Coresets via bilevel optimization for continual learning and streaming","volume":"33","author":"Borsos","year":"2020","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.neucom.2026.134024_bib0060","series-title":"Proceedings of the AAAI Conference on Artificial Intelligence","article-title":"Glister: generalization based data subset selection for efficient and robust learning","author":"Killamsetty","year":"2021"},{"key":"10.1016\/j.neucom.2026.134024_bib0065","series-title":"International Conference on Machine Learning","article-title":"Grad-match: gradient matching based data subset selection for efficient deep model training","author":"Killamsetty","year":"2021"},{"key":"10.1016\/j.neucom.2026.134024_bib0070","series-title":"International Conference on Machine Learning","article-title":"Data valuation using reinforcement learning","author":"Yoon","year":"2020"},{"key":"10.1016\/j.neucom.2026.134024_bib0075","series-title":"International Conference on Learning Representations","article-title":"Data valuation without training of a model","author":"Nohyun","year":"2023"},{"key":"10.1016\/j.neucom.2026.134024_bib0080","series-title":"The Eleventh International Conference on Learning Representations","article-title":"LAVA: data valuation without pre-specified learning algorithms","author":"Just","year":"2023"},{"key":"10.1016\/j.neucom.2026.134024_bib0085","article-title":"Active bias: training more accurate neural networks by emphasizing high variance samples","volume":"30","author":"Chang","year":"2017","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.neucom.2026.134024_bib0090","series-title":"IEEE Winter Conference on Applications of Computer Vision","article-title":"Learning from less data: a unified data subset selection and active learning framework for computer vision","author":"Kaushal","year":"2019"},{"key":"10.1016\/j.neucom.2026.134024_bib0095","series-title":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","article-title":"Data-efficient backdoor attacks","author":"Xia","year":"2022"},{"key":"10.1016\/j.neucom.2026.134024_bib0100","series-title":"International Conference on Learning Representations","article-title":"WaNet - imperceptible warping-based backdoor attack","author":"Nguyen","year":"2021"},{"key":"10.1016\/j.neucom.2026.134024_bib0105","first-page":"3454","article-title":"Input-aware dynamic backdoor attack","volume":"33","author":"Nguyen","year":"2020","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.neucom.2026.134024_bib0110","first-page":"18944","article-title":"Backdoor attack with imperceptible input and latent modification","volume":"34","author":"Doan","year":"2021","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.neucom.2026.134024_bib0115","series-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","article-title":"Lira: learnable, imperceptible and robust backdoor attacks","author":"Doan","year":"2021"},{"key":"10.1016\/j.neucom.2026.134024_bib0120","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","article-title":"BppAttack: stealthy and efficient trojan attacks against deep neural networks via image quantization and contrastive adversarial learning","author":"Wang","year":"2022"},{"key":"10.1016\/j.neucom.2026.134024_bib0125","author":"Wu"},{"key":"10.1016\/j.neucom.2026.134024_bib0130","author":"Li"},{"key":"10.1016\/j.neucom.2026.134024_bib0135","series-title":"Thirty-Sixth Conference on Neural Information Processing Systems Datasets and Benchmarks Track","article-title":"BackdoorBench: a comprehensive benchmark of backdoor learning","author":"Wu","year":"2022"},{"key":"10.1016\/j.neucom.2026.134024_bib0140","series-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","first-page":"16473","article-title":"Rethinking the backdoor attacks\u2019 triggers: a frequency perspective","author":"Zeng","year":"2021"},{"key":"10.1016\/j.neucom.2026.134024_bib0145","doi-asserted-by":"crossref","first-page":"5691","DOI":"10.1109\/TIP.2022.3201472","article-title":"Poison ink: robust and invisible backdoor attack","volume":"31","author":"Zhang","year":"2022","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.neucom.2026.134024_bib0150","series-title":"IEEE 7th European Symposium on Security and Privacy (EuroS&P)","article-title":"Dynamic backdoor attacks against machine learning models","author":"Salem","year":"2022"},{"key":"10.1016\/j.neucom.2026.134024_bib0155","author":"Turner"},{"key":"10.1016\/j.neucom.2026.134024_bib0160","first-page":"19165","article-title":"Sleeper agent: scalable hidden trigger backdoors for neural networks trained from scratch","volume":"35","author":"Souri","year":"2022","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.neucom.2026.134024_bib0165","series-title":"Thirty-Sixth Conference on Neural Information Processing Systems","article-title":"Marksman backdoor: backdoor attacks with arbitrary target class","author":"Doan","year":"2022"},{"key":"10.1016\/j.neucom.2026.134024_bib0170","article-title":"Spectral signatures in backdoor attacks","volume":"31","author":"Tran","year":"2018","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.neucom.2026.134024_bib0175","series-title":"International Conference on Learning Representations","article-title":"Backdoor defense via decoupling the training process","author":"Huang","year":"2022"},{"key":"10.1016\/j.neucom.2026.134024_bib0180","series-title":"International Conference on Learning Representations","article-title":"UNICORN: a unified backdoor trigger inversion framework","author":"Wang","year":"2023"},{"key":"10.1016\/j.neucom.2026.134024_bib0185","series-title":"Thirty-Sixth Conference on Neural Information Processing Systems","article-title":"One-shot neural backdoor erasing via adversarial weight masking","author":"Chai","year":"2022"},{"key":"10.1016\/j.neucom.2026.134024_bib0190","series-title":"The AAAI Conference on Artificial Intelligence Workshop","article-title":"Detecting backdoor attacks on deep neural networks by activation clustering","author":"Chen","year":"2019"},{"key":"10.1016\/j.neucom.2026.134024_bib0195","series-title":"AAAI Conference on Artificial Intelligence","article-title":"Defending backdoor attacks on vision transformer via patch processing","author":"Doan","year":"2023"},{"key":"10.1016\/j.neucom.2026.134024_bib0200","author":"Zeng"},{"key":"10.1016\/j.neucom.2026.134024_bib0205","series-title":"Advances in Neural Information Processing Systems, 33","first-page":"12080","article-title":"MetaPoison: practical general-purpose clean-label data poisoning","author":"Huang","year":"2020"},{"key":"10.1016\/j.neucom.2026.134024_bib0210","series-title":"International Conference on Learning Representations","article-title":"Witches\u2019 brew: industrial strength poisoning attacks in the real world","author":"Geiping","year":"2021"},{"key":"10.1016\/j.neucom.2026.134024_bib0215","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","first-page":"761","article-title":"Training region-based object detectors with online hard example mining","author":"Shrivastava","year":"2016"},{"key":"10.1016\/j.neucom.2026.134024_bib0220","series-title":"Proceedings of the IEEE International Conference on Computer Vision","first-page":"2980","article-title":"Focal loss for dense object detection","author":"Lin","year":"2017"},{"key":"10.1016\/j.neucom.2026.134024_bib0225","article-title":"The tradeoffs of large scale learning","volume":"20","author":"Bottou","year":"2007","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.neucom.2026.134024_bib0230","series-title":"International Conference on Machine Learning","first-page":"10347","article-title":"Training data-efficient image transformers & distillation through attention","author":"Touvron","year":"2021"},{"key":"10.1016\/j.neucom.2026.134024_bib0235","series-title":"Learning Multiple Layers of Features From Tiny Images","author":"Krizhevsky","year":"2009"},{"key":"10.1016\/j.neucom.2026.134024_bib0240","series-title":"Tiny ImageNet Visual Recognition Challenge","author":"Le","year":"2015"},{"key":"10.1016\/j.neucom.2026.134024_bib0245","series-title":"European Conference on Computer Vision","article-title":"Identity mappings in deep residual networks","author":"He","year":"2016"},{"key":"10.1016\/j.neucom.2026.134024_bib0250","series-title":"International Conference on Learning Representations","article-title":"Very deep convolutional networks for large-scale image recognition","author":"Simonyan","year":"2015"},{"key":"10.1016\/j.neucom.2026.134024_bib0255","author":"Howard"},{"key":"10.1016\/j.neucom.2026.134024_bib0260","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","first-page":"4700","article-title":"Densely connected convolutional networks","author":"Huang","year":"2017"},{"key":"10.1016\/j.neucom.2026.134024_bib0265","series-title":"International Symposium on Research in Attacks, Intrusions, and Defenses","article-title":"Fine-pruning: defending against backdooring attacks on deep neural networks","author":"Liu","year":"2018"},{"key":"10.1016\/j.neucom.2026.134024_bib0270","article-title":"Anti-backdoor learning: training clean models on poisoned data","volume":"34","author":"Li","year":"2021","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.neucom.2026.134024_bib0275","series-title":"European Conference on Computer Vision","article-title":"Data-free backdoor removal based on channel lipschitzness","author":"Zheng","year":"2022"},{"key":"10.1016\/j.neucom.2026.134024_bib0280","series-title":"International Conference on Learning Representations","article-title":"Neural attention distillation: erasing backdoor triggers from deep neural networks","author":"Li","year":"2020"},{"key":"10.1016\/j.neucom.2026.134024_bib0285","series-title":"International Conference on Learning Representations","article-title":"Adversarial unlearning of backdoors via implicit hypergradient","author":"Zeng","year":"2021"},{"key":"10.1016\/j.neucom.2026.134024_bib0290","series-title":"NeurIPS Workshop on Federated Learning","article-title":"Measuring the effects of non-identical data distribution for federated visual classification","author":"Hsu","year":"2019"},{"issue":"6088","key":"10.1016\/j.neucom.2026.134024_bib0295","doi-asserted-by":"crossref","first-page":"533","DOI":"10.1038\/323533a0","article-title":"Learning representations by back-propagating errors","volume":"323","author":"Rumelhart","year":"1986","journal-title":"Nature"},{"issue":"4","key":"10.1016\/j.neucom.2026.134024_bib0300","doi-asserted-by":"crossref","first-page":"600","DOI":"10.1109\/TIP.2003.819861","article-title":"Image quality assessment: from error visibility to structural similarity","volume":"13","author":"Wang","year":"2004","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.neucom.2026.134024_bib0305","series-title":"The Eleventh International Conference on Learning Representations","article-title":"Revisiting the assumption of latent separability for backdoor defenses","author":"Qi","year":"2022"},{"key":"10.1016\/j.neucom.2026.134024_bib0310","series-title":"Thirty-Sixth Conference on Neural Information Processing Systems Datasets and Benchmarks Track","article-title":"BackdoorBench: a comprehensive benchmark of backdoor learning","author":"Wu","year":"2022"},{"key":"10.1016\/j.neucom.2026.134024_bib0315","author":"Kingma"}],"container-title":["Neurocomputing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0925231226014220?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0925231226014220?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T06:34:11Z","timestamp":1781678051000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0925231226014220"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9]]},"references-count":63,"alternative-id":["S0925231226014220"],"URL":"https:\/\/doi.org\/10.1016\/j.neucom.2026.134024","relation":{},"ISSN":["0925-2312"],"issn-type":[{"value":"0925-2312","type":"print"}],"subject":[],"published":{"date-parts":[[2026,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Boosting backdoor attack with a learnable poisoning sample selection strategy","name":"articletitle","label":"Article Title"},{"value":"Neurocomputing","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.neucom.2026.134024","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"134024"}}