{"id":"https://openalex.org/W7076668801","doi":"https://doi.org/10.21227/g979-z729","title":"\"Fine-Tuned GPT Models for Covert Data Leakage Detection in UAV Networks\"","display_name":"\"Fine-Tuned GPT Models for Covert Data Leakage Detection in UAV Networks\"","publication_year":2025,"publication_date":"2025-08-19","ids":{"openalex":"https://openalex.org/W7076668801","doi":"https://doi.org/10.21227/g979-z729"},"language":"en","primary_location":{"id":"doi:10.21227/g979-z729","is_oa":true,"landing_page_url":"https://doi.org/10.21227/g979-z729","pdf_url":null,"source":{"id":"https://openalex.org/S7407051695","display_name":"IEEE DataPort","issn_l":null,"issn":[],"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","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"dataset"},"type":"dataset","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.21227/g979-z729","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Abdallah Al-Shorman","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Abdallah Al-Shorman","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T13917","display_name":"Engineering and Material Science Research","score":0.0340999998152256,"subfield":{"id":"https://openalex.org/subfields/2500","display_name":"General Materials Science"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13917","display_name":"Engineering and Material Science Research","score":0.0340999998152256,"subfield":{"id":"https://openalex.org/subfields/2500","display_name":"General Materials Science"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12773","display_name":"Water Quality and Resources Studies","score":0.03350000083446503,"subfield":{"id":"https://openalex.org/subfields/2312","display_name":"Water Science and Technology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13370","display_name":"Diverse Scientific and Economic Studies","score":0.02889999933540821,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/drone","display_name":"Drone","score":0.6473000049591064},{"id":"https://openalex.org/keywords/data-pre-processing","display_name":"Data pre-processing","score":0.4794999957084656},{"id":"https://openalex.org/keywords/covert","display_name":"Covert","score":0.4765999913215637},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.4575999975204468},{"id":"https://openalex.org/keywords/leakage","display_name":"Leakage (economics)","score":0.44920000433921814},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4156999886035919},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.3179999887943268}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6626999974250793},{"id":"https://openalex.org/C59519942","wikidata":"https://www.wikidata.org/wiki/Q650665","display_name":"Drone","level":2,"score":0.6473000049591064},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5209000110626221},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4832000136375427},{"id":"https://openalex.org/C10551718","wikidata":"https://www.wikidata.org/wiki/Q5227332","display_name":"Data pre-processing","level":2,"score":0.4794999957084656},{"id":"https://openalex.org/C2779338814","wikidata":"https://www.wikidata.org/wiki/Q5179285","display_name":"Covert","level":2,"score":0.4765999913215637},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.4575999975204468},{"id":"https://openalex.org/C2777042071","wikidata":"https://www.wikidata.org/wiki/Q6509304","display_name":"Leakage (economics)","level":2,"score":0.44920000433921814},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43560001254081726},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4156999886035919},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3179999887943268},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3174000084400177},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.31520000100135803},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.30079999566078186},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2736999988555908},{"id":"https://openalex.org/C138827492","wikidata":"https://www.wikidata.org/wiki/Q6661985","display_name":"Data processing","level":2,"score":0.27090001106262207},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.26820001006126404},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.2563999891281128},{"id":"https://openalex.org/C2779201187","wikidata":"https://www.wikidata.org/wiki/Q2775060","display_name":"Information leakage","level":2,"score":0.25369998812675476},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.25290000438690186}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.21227/g979-z729","is_oa":true,"landing_page_url":"https://doi.org/10.21227/g979-z729","pdf_url":null,"source":{"id":"https://openalex.org/S7407051695","display_name":"IEEE DataPort","issn_l":null,"issn":[],"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","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"dataset"}],"best_oa_location":{"id":"doi:10.21227/g979-z729","is_oa":true,"landing_page_url":"https://doi.org/10.21227/g979-z729","pdf_url":null,"source":{"id":"https://openalex.org/S7407051695","display_name":"IEEE DataPort","issn_l":null,"issn":[],"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","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"dataset"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"\"Abstract\\u2014The":[0],"unmanned":[1],"aerial":[2],"systems":[3],"(UAS)":[4],"in":[5,43,157],"civilian":[6],"andcommercial":[7],"applications":[8],"has":[9],"introduced":[10],"significant":[11],"cybersecuritychallenges,":[12],"particularly":[13],"concerning":[14],"data":[15,27,62],"leakage":[16,28,63],"risks":[17],"duringdrone":[18],"operations.":[19],"This":[20,136],"research":[21,137],"presents":[22],"a":[23,48,73,108,163],"novel":[24],"approach":[25],"todrone":[26],"classification":[29,86,156],"using":[30,66],"Generative":[31],"Pre-trainedTransformer":[32],"(GPT)":[33],"models,":[34],"specifically":[35],"addressing":[36],"the":[37,140,149],"criticalneed":[38],"for":[39,165],"intelligent":[40],"threat":[41],"detection":[42],"drone":[44,58],"communicationnetworks.":[45],"We":[46],"propose":[47],"comprehensive":[49],"framework":[50,161],"that":[51],"leveragesInter-Arrival":[52],"Time":[53],"(IAT)":[54],"features":[55],"extracted":[56],"from":[57],"networktraffic":[59],"to":[60,118,139,177],"classify":[61],"risk":[64],"levels":[65],"fine-tuned":[67,84,103,121],"GPTmodels.":[68],"Our":[69],"methodology":[70],"involves":[71],"preprocessing":[72],"dataset":[74],"of48,020":[75],"samples":[76],"with":[77,92,126],"14":[78],"IAT-based":[79],"features,":[80],"implementing":[81],"bothzero-shot":[82],"and":[83,114,146,169],"GPT":[85],"approaches,":[87],"andconducting":[88],"extensive":[89],"comparative":[90],"analysis":[91],"traditional":[93],"ma-chine":[94],"learning":[95],"baselines.":[96],"The":[97,120],"experimental":[98],"results":[99,116],"demonstratethat":[100],"our":[101],"GPT-based":[102],"model":[104,122],"achieves":[105],"89.2%":[106,129],"accuracy,representing":[107],"substantial":[109],"36.8%":[110],"improvement":[111],"over":[112],"zero-shotperformance":[113],"competitive":[115],"compared":[117],"traditionalapproaches.":[119],"exhibits":[123],"superior":[124],"performancemetrics":[125],"88.85%":[127],"precision,":[128],"recall,":[130],"89.02%":[131],"F1-score,and":[132],"94.56%":[133],"ROC":[134],"AUC.":[135],"contributes":[138],"in-tersection":[141],"of":[142,151],"natural":[143],"language":[144,175],"processing":[145],"cybersecurity":[147,178],"bydemonstrating":[148],"effectiveness":[150],"transformer-based":[152],"models":[153,176],"fornumerical":[154],"feature":[155],"security-critical":[158],"applications.The":[159],"proposed":[160],"provides":[162],"foundation":[164],"real-timedrone":[166],"security":[167],"monitoring":[168],"establishes":[170],"new":[171],"directions":[172],"forapplying":[173],"large":[174],"challenges":[179],"inautonomous":[180],"systems.\"":[181]},"counts_by_year":[],"updated_date":"2025-11-06T06:51:31.235846","created_date":"2025-10-10T00:00:00"}