{"id":"https://openalex.org/W4377139646","doi":"https://doi.org/10.1080/08839514.2023.2214766","title":"Waveforms Eavesdropping Prevention Framework: The Case of Classification of EPG Waveforms of Aphid Utilizing Wavelet Kernel Extreme Learning Machine","display_name":"Waveforms Eavesdropping Prevention Framework: The Case of Classification of EPG Waveforms of Aphid Utilizing Wavelet Kernel Extreme Learning Machine","publication_year":2023,"publication_date":"2023-05-19","ids":{"openalex":"https://openalex.org/W4377139646","doi":"https://doi.org/10.1080/08839514.2023.2214766"},"language":"en","primary_location":{"id":"doi:10.1080/08839514.2023.2214766","is_oa":true,"landing_page_url":"https://doi.org/10.1080/08839514.2023.2214766","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/08839514.2023.2214766?download=true","source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.tandfonline.com/doi/pdf/10.1080/08839514.2023.2214766?download=true","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5052160451","display_name":"Yuqing Xing","orcid":null},"institutions":[{"id":"https://openalex.org/I169689159","display_name":"PLA Information Engineering University","ror":"https://ror.org/00mm1qk40","country_code":"CN","type":"education","lineage":["https://openalex.org/I169689159"]},{"id":"https://openalex.org/I4750791","display_name":"Henan Agricultural University","ror":"https://ror.org/04eq83d71","country_code":"CN","type":"education","lineage":["https://openalex.org/I4750791"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuqing Xing","raw_affiliation_strings":["College of Sciences, Henan Agricultural University, Zhengzhou, China","School of Cybersecurity, Information Engineering University, Zhengzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Sciences, Henan Agricultural University, Zhengzhou, China","institution_ids":["https://openalex.org/I4750791"]},{"raw_affiliation_string":"School of Cybersecurity, Information Engineering University, Zhengzhou, China","institution_ids":["https://openalex.org/I169689159"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085223449","display_name":"Baofang Li","orcid":"https://orcid.org/0009-0002-3647-5182"},"institutions":[{"id":"https://openalex.org/I4750791","display_name":"Henan Agricultural University","ror":"https://ror.org/04eq83d71","country_code":"CN","type":"education","lineage":["https://openalex.org/I4750791"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Baofang Li","raw_affiliation_strings":["College of Sciences, Henan Agricultural University, Zhengzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Sciences, Henan Agricultural University, Zhengzhou, China","institution_ids":["https://openalex.org/I4750791"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014801174","display_name":"Lili Wu","orcid":"https://orcid.org/0000-0002-1319-7274"},"institutions":[{"id":"https://openalex.org/I4750791","display_name":"Henan Agricultural University","ror":"https://ror.org/04eq83d71","country_code":"CN","type":"education","lineage":["https://openalex.org/I4750791"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lili Wu","raw_affiliation_strings":["College of Sciences, Henan Agricultural University, Zhengzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Sciences, Henan Agricultural University, Zhengzhou, China","institution_ids":["https://openalex.org/I4750791"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109297729","display_name":"Fengming Yan","orcid":null},"institutions":[{"id":"https://openalex.org/I4750791","display_name":"Henan Agricultural University","ror":"https://ror.org/04eq83d71","country_code":"CN","type":"education","lineage":["https://openalex.org/I4750791"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fengming Yan","raw_affiliation_strings":["College of Plant Protection, Henan Agricultural University, Zhengzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Plant Protection, Henan Agricultural University, Zhengzhou, China","institution_ids":["https://openalex.org/I4750791"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5014801174"],"corresponding_institution_ids":["https://openalex.org/I4750791"],"apc_list":{"value":2195,"currency":"USD","value_usd":2195},"apc_paid":{"value":2195,"currency":"USD","value_usd":2195},"fwci":0.7931,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.75785147,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":"37","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9868000149726868,"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/T12676","display_name":"Machine Learning and ELM","score":0.9868000149726868,"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/T10558","display_name":"Advancements in Semiconductor Devices and Circuit Design","score":0.9444000124931335,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9186999797821045,"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/computer-science","display_name":"Computer science","score":0.8271325826644897},{"id":"https://openalex.org/keywords/waveform","display_name":"Waveform","score":0.6659031510353088},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5571653842926025},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49901628494262695},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.480591744184494},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.4580366611480713},{"id":"https://openalex.org/keywords/eavesdropping","display_name":"Eavesdropping","score":0.4160744845867157},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.15513944625854492},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.151895672082901},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.1110365092754364}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8271325826644897},{"id":"https://openalex.org/C197424946","wikidata":"https://www.wikidata.org/wiki/Q1165717","display_name":"Waveform","level":3,"score":0.6659031510353088},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5571653842926025},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49901628494262695},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.480591744184494},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.4580366611480713},{"id":"https://openalex.org/C2776788033","wikidata":"https://www.wikidata.org/wiki/Q320769","display_name":"Eavesdropping","level":2,"score":0.4160744845867157},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.15513944625854492},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.151895672082901},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.1110365092754364}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1080/08839514.2023.2214766","is_oa":true,"landing_page_url":"https://doi.org/10.1080/08839514.2023.2214766","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/08839514.2023.2214766?download=true","source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:79f4b87519b34fd3b1c427704dfa69bb","is_oa":true,"landing_page_url":"https://doaj.org/article/79f4b87519b34fd3b1c427704dfa69bb","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Applied Artificial Intelligence, Vol 37, Iss 1 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1080/08839514.2023.2214766","is_oa":true,"landing_page_url":"https://doi.org/10.1080/08839514.2023.2214766","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/08839514.2023.2214766?download=true","source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2288254378","display_name":null,"funder_award_id":"18A510012","funder_id":"https://openalex.org/F4320335955","funder_display_name":"Key Scientific Research Project of Colleges and Universities in Henan Province"},{"id":"https://openalex.org/G7951813365","display_name":null,"funder_award_id":"18210211033","funder_id":"https://openalex.org/F4320327051","funder_display_name":"Science and Technology Department of Henan Province"}],"funders":[{"id":"https://openalex.org/F4320325562","display_name":"Henan Agricultural University","ror":"https://ror.org/04eq83d71"},{"id":"https://openalex.org/F4320327051","display_name":"Science and Technology Department of Henan Province","ror":null},{"id":"https://openalex.org/F4320335955","display_name":"Key Scientific Research Project of Colleges and Universities in Henan Province","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4377139646.pdf","grobid_xml":"https://content.openalex.org/works/W4377139646.grobid-xml"},"referenced_works_count":21,"referenced_works":["https://openalex.org/W1128650025","https://openalex.org/W1990417042","https://openalex.org/W1990938413","https://openalex.org/W2047624378","https://openalex.org/W2064340692","https://openalex.org/W2079385189","https://openalex.org/W2098290011","https://openalex.org/W2105628623","https://openalex.org/W2109715919","https://openalex.org/W2154196451","https://openalex.org/W2529692997","https://openalex.org/W2579951724","https://openalex.org/W2751033988","https://openalex.org/W2792700024","https://openalex.org/W2883617859","https://openalex.org/W2901544499","https://openalex.org/W3042922486","https://openalex.org/W3100450904","https://openalex.org/W3124013922","https://openalex.org/W4200476547","https://openalex.org/W4226028831"],"related_works":["https://openalex.org/W4387918499","https://openalex.org/W2772112465","https://openalex.org/W4386360526","https://openalex.org/W2368710903","https://openalex.org/W2158905603","https://openalex.org/W2766105476","https://openalex.org/W2735171729","https://openalex.org/W2769254131","https://openalex.org/W2091556092","https://openalex.org/W2908395774"],"abstract_inverted_index":{"Since":[0],"all":[1,245],"information":[2],"depends":[3],"solely":[4],"on":[5,106,150],"the":[6,22,95,107,120,125,157,169,176,196,202,212,221,226,232,241,249,254,261],"training":[7],"data,":[8],"machine":[9,27,138],"learning":[10,23,28,112,139],"algorithms":[11],"typically":[12],"do":[13],"not":[14],"employ":[15],"external":[16],"knowledge":[17],"or":[18,41,258],"other":[19],"experiences":[20],"during":[21],"process.":[24],"Methods":[25],"for":[26,78,162,167],"have":[29],"been":[30],"rigorously":[31],"tested":[32],"against":[33],"novel":[34],"varieties":[35],"of":[36,110,172,190,201,225,256],"highly":[37],"technical":[38],"\u201cblack":[39],"box\u201d":[40,43],"\u201cwhite":[42],"adversarial":[44,236],"attacks.":[45],"By":[46,114],"employing":[47],"attacks,":[48],"attackers":[49],"can":[50],"change":[51],"systems":[52],"to":[53,71,81,136,141,155,230],"serve":[54],"a":[55,87,93,99,111,116,151,164],"harmful":[56],"end":[57],"goal.":[58],"When":[59],"authorized":[60],"implementers":[61],"and":[62,175,181,198,216],"eavesdroppers":[63],"are":[64],"geographically":[65],"close":[66],"together,":[67],"it":[68],"is":[69,148],"difficult":[70],"perform":[72],"secure":[73],"beamforming":[74],"in":[75,98,132,195,220,252,264],"waveform":[76,108,246],"applications,":[77],"instance,":[79],"leading":[80],"erroneous":[82],"beam":[83,90],"forms":[84],"and,":[85],"as":[86],"result,":[88,94],"disastrous":[89],"leakages.":[91],"As":[92],"first":[96,222],"move":[97],"prospective":[100],"black-box":[101],"offense":[102],"will":[103],"be":[104],"based":[105,149],"features":[109],"signal.":[113],"including":[115],"non-orthogonality":[117],"concept":[118],"into":[119],"physical":[121],"layer":[122],"signal":[123],"waveform,":[124],"Waveforms":[126],"Eavesdropping":[127],"Prevention":[128],"Framework":[129],"(WEPF)":[130],"proposed":[131,233],"this":[133],"work":[134],"aims":[135],"boost":[137],"security":[140],"address":[142],"these":[143],"difficulties.":[144],"The":[145],"implementation":[146],"scenario":[147,153],"waveforms":[152,262],"used":[154,229,263],"categorize":[156],"Electrical":[158],"Penetration":[159],"Graph":[160],"(EPG)":[161],"insects,":[163],"crucial":[165],"tool":[166],"researching":[168],"feeding":[170],"conduct":[171],"piercing-sucking":[173],"insects":[174],"transition":[177],"mechanism":[178],"between":[179],"viruses":[180],"insects.":[182],"An":[183],"attribute":[184],"vector":[185],"with":[186,260],"six":[187],"dimensions,":[188],"consisting":[189],"low-frequency":[191],"wavelet":[192],"energy":[193],"(LFWE)":[194],"second":[197],"third":[199],"layers":[200,224],"Wavelet":[203],"Kernel":[204],"Extreme":[205],"Learning":[206],"Machine,":[207],"fractal":[208],"box":[209],"dimension":[210],"(FBD),":[211],"Hurst":[213],"exponent":[214],"(HE),":[215],"spectral":[217],"centroid":[218],"(SC)":[219],"two":[223],"HHT,":[227],"was":[228],"test":[231],"framework.":[234],"Two":[235],"scenarios":[237],"were":[238],"explored.":[239],"However,":[240],"suggested":[242],"architecture":[243],"secures":[244],"signals,":[247],"demonstrating":[248],"method\u2019s":[250],"effectiveness":[251],"lowering":[253],"risk":[255],"eavesdropping":[257],"tampering":[259],"advanced":[265],"machine-learning":[266],"methods.":[267]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3}],"updated_date":"2026-03-07T13:37:22.277990","created_date":"2025-10-10T00:00:00"}
