{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,18]],"date-time":"2025-11-18T07:48:34Z","timestamp":1763452114975,"version":"3.45.0"},"reference-count":30,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2025,11,12]],"date-time":"2025-11-12T00:00:00Z","timestamp":1762905600000},"content-version":"vor","delay-in-days":11,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Security and Privacy"],"published-print":{"date-parts":[[2025,11]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>In order to improve the capability of black\u2010box local attack, a black\u2010box local attack method based on the improved BANA algorithm is proposed. First, based on the BANA algorithm, an autoencoder is introduced to generate an initial population of random perturbations. Then, by improving the crossover and mutation operations of the BANA algorithm, high\u2010quality adversarial samples are generated, achieving fast and effective black\u2010box local attacks. Simulation results reveal that the average fooling rate, average L2 norm length, average query time, average peak signal\u2010to\u2010noise ratio, and average structural similarity of the black\u2010box local attack method based on the improved BANA algorithm are 100%, 1.26, 92.00, 0.94\u2009dB, and 33.70%, respectively. The fooling rate, average L2 norm length, average query times, peak signal\u2010to\u2010noise ratio of adversarial examples, and average structural similarity of the adversarial examples of the neural network model for distillation defense are 98.33%, 1.32, 98.63, 0.92\u2009dB, and 30.14%, respectively. Therefore, the black\u2010box local attack method based on the improved BANA algorithm has a high black\u2010box local attack ability.<\/jats:p>","DOI":"10.1002\/spy2.70132","type":"journal-article","created":{"date-parts":[[2025,11,12]],"date-time":"2025-11-12T13:44:18Z","timestamp":1762955058000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Research on Black\u2010Box Local Attack Methods Based on Improved\n                    <scp>BANA<\/scp>\n                    Algorithm"],"prefix":"10.1002","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-3868-4632","authenticated-orcid":false,"given":"Jiang","family":"Wu","sequence":"first","affiliation":[{"name":"School of Optical\u2010Electrical and Communication Engineering Yunnan Open University  Kunming China"}]}],"member":"311","published-online":{"date-parts":[[2025,11,12]]},"reference":[{"issue":"11","key":"e_1_2_7_2_1","first-page":"1","article-title":"Electromagnetic Countermeasure Attack Based on Variational Encoder and Principal Component Analysis","volume":"52","author":"He K.","year":"2024","journal-title":"Journal of Huazhong University of Science and Technology (Natural Science Edition)"},{"issue":"2","key":"e_1_2_7_3_1","first-page":"24","article-title":"A Black Box Algorithm for Random Beam Search Text Attack","volume":"47","author":"Wang X. 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