{"id":"https://openalex.org/W7163892919","doi":"https://doi.org/10.48550/arxiv.2606.06501","title":"Enhancing Malware Detection with Generative AI: Using Variational Autoencoders to Boost Machine Learning Classifiers' Performance","display_name":"Enhancing Malware Detection with Generative AI: Using Variational Autoencoders to Boost Machine Learning Classifiers' Performance","publication_year":2026,"publication_date":"2026-05-17","ids":{"openalex":"https://openalex.org/W7163892919","doi":"https://doi.org/10.48550/arxiv.2606.06501"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.06501","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.06501","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.06501","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5138170874","display_name":"Mohammad Alharbi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Alharbi, Mohammad","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5074333355","display_name":"Jeremy Straub","orcid":"https://orcid.org/0000-0002-9821-2858"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Straub, Jeremy","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"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":false,"primary_topic":{"id":"https://openalex.org/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9696000218391418,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9696000218391418,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.010099999606609344,"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"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.003100000089034438,"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/malware","display_name":"Malware","score":0.8375999927520752},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.5730000138282776},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5171999931335449},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.3962000012397766},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.3950999975204468},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.35109999775886536}],"concepts":[{"id":"https://openalex.org/C541664917","wikidata":"https://www.wikidata.org/wiki/Q14001","display_name":"Malware","level":2,"score":0.8375999927520752},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.795799970626831},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.7803999781608582},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7699999809265137},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5730000138282776},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5171999931335449},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.3962000012397766},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.3950999975204468},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.35109999775886536},{"id":"https://openalex.org/C2778403875","wikidata":"https://www.wikidata.org/wiki/Q20312394","display_name":"Adversarial machine learning","level":3,"score":0.3224000036716461},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3027999997138977},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.28999999165534973},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.2827000021934509},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.2705000042915344},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.26489999890327454},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.25119999051094055}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.06501","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.06501","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.06501","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.06501","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0,83,100,135,159],"advancement":[1],"of":[2,11,27,61,102,112,148,170,186],"malware":[3,22,52,69,98,165,178,206],"poses":[4],"obstacles":[5],"for":[6,64,162,189,196],"cybersecurity,":[7],"necessitating":[8],"the":[9,25,40,58,110,113,122,131,142,149,156,168,184],"development":[10],"advanced":[12],"detection":[13,23,207],"techniques.":[14],"This":[15,71,181],"paper":[16],"proposes":[17],"an":[18],"approach":[19,72,172],"to":[20,56,76,79,88,173,176],"enhance":[21],"through":[24],"use":[26],"a":[28,138,194],"generative":[29,187],"artificial":[30],"intelligence":[31],"model.":[32],"Specifically,":[33],"variational":[34],"autoencoders":[35],"(VAEs)":[36],"are":[37,54,119,128,153],"used":[38,55,75],"with":[39,121,130],"random":[41],"forest,":[42],"XGBoost":[43],"and":[44,125,146,204],"sequential":[45],"model":[46],"machine":[47,114],"learning":[48,115],"classifiers.":[49],"Generated":[50],"synthetic":[51,92,132],"samples":[53],"address":[57],"critical":[59],"issue":[60],"data":[62,124],"scarcity":[63],"new":[65],"or":[66],"less":[67],"common":[68],"types.":[70],"can":[73],"be":[74],"augment":[77],"datasets":[78,93,105],"improve":[80],"classifier":[81],"robustness.":[82],"proposed":[84],"methodology":[85],"uses":[86],"VAEs":[87],"create":[89],"high-quality":[90],"diverse":[91],"that":[94],"closely":[95],"mimic":[96],"real-world":[97],"data.":[99],"effectiveness":[101],"these":[103],"augmented":[104,157],"is":[106],"evaluated":[107],"by":[108],"comparing":[109],"performance":[111,161],"classifiers":[116],"when":[117,126,151],"they":[118,127,152],"trained":[120,129,154],"original":[123],"data-augmented":[133],"datasets.":[134,158],"results":[136],"demonstrate":[137],"notable":[139],"improvement":[140],"in":[141],"accuracy,":[143],"precision,":[144],"recall":[145],"F1-scores":[147],"classifiers,":[150],"using":[155],"enhanced":[160],"detecting":[163],"various":[164],"classes":[166],"shows":[167],"potential":[169],"this":[171],"facilitate":[174],"adaptation":[175],"evolving":[177],"threats":[179],"effectively.":[180],"work":[182],"demonstrates":[183],"utility":[185],"AI":[188],"cybersecurity.":[190],"It":[191],"also":[192],"provides":[193],"foundation":[195],"future":[197],"research":[198],"aimed":[199],"at":[200],"developing":[201],"more":[202],"resilient":[203],"adaptive":[205],"systems.":[208]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-09T00:00:00"}
