{"id":"https://openalex.org/W4413125880","doi":"https://doi.org/10.1109/taes.2025.3596956","title":"Toward Model-Agnostic Adversarial Attack With Scattering Similarity for CNN-SAR Recognition","display_name":"Toward Model-Agnostic Adversarial Attack With Scattering Similarity for CNN-SAR Recognition","publication_year":2025,"publication_date":"2025-08-07","ids":{"openalex":"https://openalex.org/W4413125880","doi":"https://doi.org/10.1109/taes.2025.3596956"},"language":"en","primary_location":{"id":"doi:10.1109/taes.2025.3596956","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taes.2025.3596956","pdf_url":null,"source":{"id":"https://openalex.org/S193624734","display_name":"IEEE Transactions on Aerospace and Electronic Systems","issn_l":"0018-9251","issn":["0018-9251","1557-9603","2371-9877"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Aerospace and Electronic Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Weibo Qin","orcid":"https://orcid.org/0009-0005-2528-6230"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weibo Qin","raw_affiliation_strings":["Key Laboratory for Information Science of Electromagnetic Waves (Ministry of Education), School of Information Science and Technology, Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0005-2528-6230","affiliations":[{"raw_affiliation_string":"Key Laboratory for Information Science of Electromagnetic Waves (Ministry of Education), School of Information Science and Technology, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059017196","display_name":"Bo Long","orcid":"https://orcid.org/0009-0006-5591-8216"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Long","raw_affiliation_strings":["Key Laboratory for Information Science of Electromagnetic Waves (Ministry of Education), School of Information Science and Technology, Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0006-5591-8216","affiliations":[{"raw_affiliation_string":"Key Laboratory for Information Science of Electromagnetic Waves (Ministry of Education), School of Information Science and Technology, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"last","author":{"id":null,"display_name":"Feng Wang","orcid":"https://orcid.org/0000-0002-2378-9126"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Wang","raw_affiliation_strings":["Key Laboratory for Information Science of Electromagnetic Waves (Ministry of Education), School of Information Science and Technology, Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-2378-9126","affiliations":[{"raw_affiliation_string":"Key Laboratory for Information Science of Electromagnetic Waves (Ministry of Education), School of Information Science and Technology, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I24943067"],"apc_list":null,"apc_paid":null,"fwci":2.792,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.91346373,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":"61","issue":"6","first_page":"16708","last_page":"16723"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9926999807357788,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9926999807357788,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.965499997138977,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.939300000667572,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.7516887187957764},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6839388012886047},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.6043715476989746},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5401309132575989},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.4861833453178406},{"id":"https://openalex.org/keywords/radar-imaging","display_name":"Radar imaging","score":0.44584691524505615},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43662089109420776},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.3435326814651489},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.16435933113098145},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.10881099104881287}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.7516887187957764},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6839388012886047},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6043715476989746},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5401309132575989},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.4861833453178406},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.44584691524505615},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43662089109420776},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.3435326814651489},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.16435933113098145},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.10881099104881287}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/taes.2025.3596956","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taes.2025.3596956","pdf_url":null,"source":{"id":"https://openalex.org/S193624734","display_name":"IEEE Transactions on Aerospace and Electronic Systems","issn_l":"0018-9251","issn":["0018-9251","1557-9603","2371-9877"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Aerospace and Electronic Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.41999998688697815,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G3069370439","display_name":"\u5e8f\u5217ISAR\u6210\u50cf\u6563\u5c04\u673a\u5236\u5efa\u6a21\u4e0e\u4e09\u7ef4\u4fe1\u606f\u83b7\u53d6","funder_award_id":"20ZR1406300","funder_id":"https://openalex.org/F4320309612","funder_display_name":"Natural Science Foundation of Shanghai"},{"id":"https://openalex.org/G796721411","display_name":null,"funder_award_id":"61991421","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320309612","display_name":"Natural Science Foundation of Shanghai","ror":null},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1965572316","https://openalex.org/W2158672843","https://openalex.org/W2169164332","https://openalex.org/W2194775991","https://openalex.org/W2333122909","https://openalex.org/W2410591237","https://openalex.org/W2616247523","https://openalex.org/W2621042270","https://openalex.org/W2746600820","https://openalex.org/W2754361766","https://openalex.org/W2774644650","https://openalex.org/W2895097814","https://openalex.org/W2904480641","https://openalex.org/W2945014618","https://openalex.org/W2963446712","https://openalex.org/W2963542245","https://openalex.org/W2981892732","https://openalex.org/W3092021058","https://openalex.org/W3100144085","https://openalex.org/W3103836116","https://openalex.org/W3107235539","https://openalex.org/W3130760752","https://openalex.org/W3138516171","https://openalex.org/W4285133336","https://openalex.org/W4285295676","https://openalex.org/W4303649662","https://openalex.org/W4304701424","https://openalex.org/W4310854133","https://openalex.org/W4312869499","https://openalex.org/W4323338444","https://openalex.org/W4387802579","https://openalex.org/W4402401683","https://openalex.org/W4403917825"],"related_works":["https://openalex.org/W2545123933","https://openalex.org/W2585813813","https://openalex.org/W2041414401","https://openalex.org/W2042726296","https://openalex.org/W2096748030","https://openalex.org/W3016428515","https://openalex.org/W2160730947","https://openalex.org/W2747205507","https://openalex.org/W2917196883","https://openalex.org/W1908997176"],"abstract_inverted_index":{"Combined":[0],"with":[1,76,158],"an":[2],"intelligence":[3],"interpretation":[4],"system,":[5],"synthetic":[6,140,148],"aperture":[7,149],"radar":[8,150],"(SAR)":[9],"automatic":[10],"target":[11,135],"recognition":[12,138],"has":[13],"achieved":[14],"promising":[15],"progress.":[16],"Simultaneously,":[17],"the":[18,27,59,70,107,111,117,164],"existence":[19],"of":[20,61,72,106,119,166],"adversarial":[21,77,90,167],"attack":[22,47,78,155],"brings":[23],"security":[24],"problems,":[25],"and":[26,133,137,141,146],"invisible":[28],"perturbation":[29],"can":[30,51],"fool":[31],"convolutional":[32],"neural":[33],"network":[34],"(CNNs)":[35],"trained":[36],"on":[37,58,116,131],"SAR":[38],"images.":[39],"In":[40],"this":[41],"article,":[42],"a":[43,80,100,126],"query-based":[44,95],"scattering":[45,62,84,120],"model":[46],"is":[48,92,110],"proposed,":[49],"which":[50,161],"effectively":[52],"deceive":[53],"black-box":[54],"CNN-SAR":[55],"recognition.":[56],"Based":[57],"difference":[60,118],"similarity":[63,121],"from":[64,69],"various":[65],"targets,":[66],"confusable":[67],"targets":[68,123],"perspective":[71],"distribution":[73],"are":[74],"combined":[75],"as":[79,86],"strong":[81],"prior.":[82],"Then,":[83],"model,":[85],"basic":[87],"components":[88],"for":[89],"attack,":[91],"determined":[93],"by":[94,99],"generation":[96,112],"strategy,":[97],"guided":[98],"model-agnostic":[101],"criterion.":[102],"The":[103],"main":[104],"advantage":[105],"proposed":[108],"method":[109],"criterion":[113],"that":[114],"relies":[115],"between":[122],"rather":[124],"than":[125],"surrogate":[127],"model.":[128],"Experimental":[129],"results":[130],"moving":[132],"stationary":[134],"acquisition":[136],"(MSTAR),":[139],"measured":[142],"paired":[143],"labeled":[144],"experiment,":[145],"FUdan":[147],"(FUSAR)-ship":[151],"datasets":[152],"demonstrate":[153],"better":[154],"performance":[156],"compared":[157],"current":[159],"methods,":[160],"greatly":[162],"extends":[163],"application":[165],"scatterers.":[168]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-07-13T07:31:44.756512","created_date":"2025-10-10T00:00:00"}
