{"id":"https://openalex.org/W4411016642","doi":"https://doi.org/10.1145/3728725.3728788","title":"Spectrum anomaly detection and defense algorithm based on attention mechanism residual neural network","display_name":"Spectrum anomaly detection and defense algorithm based on attention mechanism residual neural network","publication_year":2025,"publication_date":"2025-02-21","ids":{"openalex":"https://openalex.org/W4411016642","doi":"https://doi.org/10.1145/3728725.3728788"},"language":"en","primary_location":{"id":"doi:10.1145/3728725.3728788","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3728725.3728788","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3728725.3728788","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 2nd International Conference on Generative Artificial Intelligence and Information Security","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3728725.3728788","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Liangjie Wang","orcid":"https://orcid.org/0009-0003-9704-8480"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liangjie Wang","raw_affiliation_strings":["School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou, Henan, China"],"raw_orcid":"https://orcid.org/0009-0003-9704-8480","affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou, Henan, China","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101786466","display_name":"Zhongyong Wang","orcid":"https://orcid.org/0000-0002-9217-6200"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhongyong Wang","raw_affiliation_strings":["School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou, Henan, China"],"raw_orcid":"https://orcid.org/0000-0002-9217-6200","affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou, Henan, China","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065846996","display_name":"Huipeng Zhai","orcid":null},"institutions":[{"id":"https://openalex.org/I4210108629","display_name":"Computer Network Information Center","ror":"https://ror.org/01s0wyf50","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210108629"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huipeng Zhai","raw_affiliation_strings":["National Computer Network and Information Security Center Henan Branch, Zhengzhou, Henan, China"],"raw_orcid":"https://orcid.org/0009-0003-3654-0359","affiliations":[{"raw_affiliation_string":"National Computer Network and Information Security Center Henan Branch, Zhengzhou, Henan, China","institution_ids":["https://openalex.org/I4210108629"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Po Hu","orcid":"https://orcid.org/0009-0002-9857-9147"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Po Hu","raw_affiliation_strings":["School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou, Henan, China"],"raw_orcid":"https://orcid.org/0009-0002-9857-9147","affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou, Henan, China","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101808943","display_name":"Wei Wang","orcid":"https://orcid.org/0000-0003-1639-4692"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Wang","raw_affiliation_strings":["School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou, Henan, China"],"raw_orcid":"https://orcid.org/0000-0003-1639-4692","affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou, Henan, China","institution_ids":["https://openalex.org/I38877650"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.05295468,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"399","last_page":"404"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.7494999766349792,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.7494999766349792,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.736299991607666,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/residual","display_name":"Residual","score":0.7804200649261475},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.6381444931030273},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6321342587471008},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5911909341812134},{"id":"https://openalex.org/keywords/mechanism","display_name":"Mechanism (biology)","score":0.5620805025100708},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.5243247747421265},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4273309111595154},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36932599544525146},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.08427974581718445}],"concepts":[{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.7804200649261475},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6381444931030273},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6321342587471008},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5911909341812134},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.5620805025100708},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.5243247747421265},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4273309111595154},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36932599544525146},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.08427974581718445},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3728725.3728788","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3728725.3728788","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3728725.3728788","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 2nd International Conference on Generative Artificial Intelligence and Information Security","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3728725.3728788","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3728725.3728788","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3728725.3728788","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 2nd International Conference on Generative Artificial Intelligence and Information Security","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.550000011920929,"display_name":"Climate action","id":"https://metadata.un.org/sdg/13"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4411016642.pdf","grobid_xml":"https://content.openalex.org/works/W4411016642.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2806741695","https://openalex.org/W4290647774","https://openalex.org/W3189286258","https://openalex.org/W3207797160","https://openalex.org/W3210364259","https://openalex.org/W4300558037","https://openalex.org/W2667207928","https://openalex.org/W2912112202","https://openalex.org/W4377864969","https://openalex.org/W3120251014"],"abstract_inverted_index":{"Spectrum":[0],"anomaly":[1,53],"detection":[2,23,54,158],"involves":[3],"identifying":[4],"abnormal":[5,17,156],"signals":[6,18],"within":[7],"the":[8,34,41,69,80,85,108,122,126,132,147,152,167,170,175,182,190,195],"electromagnetic":[9],"spectrum.":[10],"Most":[11],"existing":[12,44],"methods":[13],"focus":[14],"on":[15,57,181,201],"traditional":[16],"and":[19,27,84,98,102,138,162,173,192],"can":[20,66],"achieve":[21],"high":[22],"rates":[24],"through":[25],"training":[26],"testing":[28],"of":[29,36,43,71,125,169,178,194],"neural":[30,61,183,197],"network":[31,45,62,72,171,184,198],"models.":[32,46],"However,":[33],"presence":[35],"adversarial":[37,75,144,179],"samples":[38,180],"greatly":[39],"reduces":[40],"performance":[42,124],"To":[47],"address":[48],"this":[49],"issue,":[50],"a":[51],"spectrum":[52],"algorithm":[55,128,149],"based":[56,141,200],"attention":[58,81,104,110,202],"mechanism":[59,82,105],"residual":[60,196],"is":[63,129],"proposed,":[64],"which":[65],"significantly":[67],"improve":[68],"robustness":[70,168],"models":[73],"without":[74],"training.":[76],"This":[77],"method":[78],"integrates":[79],"module":[83],"Residual":[86],"Network":[87],"(ResNet),":[88],"using":[89,103],"ResNet18":[90,137],"to":[91,106,111,131],"process":[92],"spectrogram":[93,115],"data,":[94],"avoiding":[95],"gradient":[96],"vanishing":[97],"overfitting":[99],"during":[100],"iteration,":[101],"enhance":[107],"model's":[109],"local":[112],"information":[113],"in":[114],"data.":[116],"The":[117,186],"experimental":[118,187],"results":[119,188],"show":[120],"that":[121],"predictive":[123],"proposed":[127],"superior":[130],"compared":[133],"algorithms.":[134],"Compared":[135],"with":[136],"feature":[139],"transformation":[140],"image":[142],"retrieval":[143],"defense":[145],"algorithms,":[146],"new":[148],"has":[150],"increased":[151],"AUC":[153],"value":[154],"for":[155],"signal":[157],"by":[159],"approximately":[160],"47%":[161],"24%,":[163],"respectively,":[164],"effectively":[165],"improving":[166],"model":[172,199],"reducing":[174],"negative":[176],"impact":[177],"model.":[185],"verify":[189],"effectiveness":[191],"superiority":[193],"mechanism.":[203]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}