{"id":"https://openalex.org/W7166650474","doi":"https://doi.org/10.48550/arxiv.2606.30572","title":"A Multi-task Mixture of Experts Framework for Malware Classification, Packing Detection, and Family Attribution","display_name":"A Multi-task Mixture of Experts Framework for Malware Classification, Packing Detection, and Family Attribution","publication_year":2026,"publication_date":"2026-06-29","ids":{"openalex":"https://openalex.org/W7166650474","doi":"https://doi.org/10.48550/arxiv.2606.30572"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.30572","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.30572","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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.2606.30572","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5139647093","display_name":"Jithin S.","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"S., Jithin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139632922","display_name":"Roshin Sleeba C.","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"C., Roshin Sleeba","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139689273","display_name":"Anvin Mariya P. B.","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"B., Anvin Mariya P.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139635712","display_name":"Asmitha K. A.","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"A., Asmitha K.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139635737","display_name":"Vinod P.","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"P., Vinod","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038688486","display_name":"Serena Nicolazzo","orcid":"https://orcid.org/0000-0003-2719-9526"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nicolazzo, Serena","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5085793134","display_name":"Antonino Nocera","orcid":"https://orcid.org/0000-0003-2120-2341"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nocera, Antonino","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":0.984000027179718,"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":0.984000027179718,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.002899999963119626,"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":0.00279999990016222,"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/malware","display_name":"Malware","score":0.8669999837875366},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.626800000667572},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5701000094413757},{"id":"https://openalex.org/keywords/executable","display_name":"Executable","score":0.5002999901771545},{"id":"https://openalex.org/keywords/feature-engineering","display_name":"Feature engineering","score":0.38420000672340393},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.3752000033855438},{"id":"https://openalex.org/keywords/byte","display_name":"Byte","score":0.3296999931335449},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.3199000060558319}],"concepts":[{"id":"https://openalex.org/C541664917","wikidata":"https://www.wikidata.org/wiki/Q14001","display_name":"Malware","level":2,"score":0.8669999837875366},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.766700029373169},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.626800000667572},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5701000094413757},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5055999755859375},{"id":"https://openalex.org/C160145156","wikidata":"https://www.wikidata.org/wiki/Q778586","display_name":"Executable","level":2,"score":0.5002999901771545},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43779999017715454},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.38420000672340393},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3765999972820282},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3752000033855438},{"id":"https://openalex.org/C43364308","wikidata":"https://www.wikidata.org/wiki/Q8799","display_name":"Byte","level":2,"score":0.3296999931335449},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.3199000060558319},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.31619998812675476},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.3018999993801117},{"id":"https://openalex.org/C2778579508","wikidata":"https://www.wikidata.org/wiki/Q722192","display_name":"System call","level":2,"score":0.3009999990463257},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.2976999878883362},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.28929999470710754},{"id":"https://openalex.org/C2779395397","wikidata":"https://www.wikidata.org/wiki/Q15731404","display_name":"Malware analysis","level":3,"score":0.28209999203681946},{"id":"https://openalex.org/C2779696439","wikidata":"https://www.wikidata.org/wiki/Q7512811","display_name":"Signature (topology)","level":2,"score":0.26969999074935913},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.2680000066757202},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.260699987411499},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.25850000977516174},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.25619998574256897},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.25589999556541443}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.30572","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.30572","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.30572","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.30572","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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":{"Malware":[0],"classification":[1],"remains":[2],"a":[3,51,172,213],"challenging":[4],"problem":[5,110],"due":[6],"to":[7,29,36],"its":[8],"inherent":[9],"heterogeneity,":[10],"the":[11,17,109,120,163,168,196,210],"presence":[12],"of":[13,20,60,176,198],"packed":[14,98],"binaries,":[15],"and":[16,42,79,102,115,140,150,155,201,218],"diverse":[18,33],"distribution":[19,191],"malware":[21,44,54,95,103,207,220],"families.":[22],"Traditional":[23],"single-model":[24],"detection":[25,174,221],"mechanisms":[26],"often":[27],"fail":[28],"generalize":[30],"across":[31,69],"such":[32],"data,":[34],"leading":[35],"degraded":[37],"performance,":[38,170],"particularly":[39],"on":[40,58],"obfuscated":[41],"rare":[43],"samples.":[45,157],"In":[46],"this":[47,184],"work,":[48],"we":[49],"propose":[50],"unified":[52],"multi-task":[53],"analysis":[55],"framework":[56,212],"based":[57],"Mixture":[59],"Experts":[61],"(MoE)":[62],"architectures.":[63],"The":[64,158],"proposed":[65,211],"system":[66],"evaluates":[67],"performance":[68],"two":[70],"different":[71],"input":[72],"representations,":[73],"i.e.,":[74],"high-dimensional":[75],"EMBER":[76],"feature":[77],"sets":[78],"raw":[80],"1D":[81],"byte":[82],"arrays":[83],"extracted":[84],"from":[85],"Portable":[86],"Executable":[87],"files.":[88],"It":[89],"simultaneously":[90],"performs":[91],"three":[92],"critical":[93],"tasks:":[94],"family":[96],"classification,":[97],"versus":[99,104],"unpacked":[100],"detection,":[101],"benign":[105],"identification.":[106],"By":[107],"decomposing":[108],"into":[111],"specialized":[112],"expert":[113,199],"networks":[114],"employing":[116],"adaptive":[117],"gating":[118],"mechanisms,":[119],"model":[121,166],"enables":[122],"effective":[123],"task-specific":[124,202],"learning":[125],"while":[126],"maintaining":[127],"overall":[128],"scalability.":[129],"We":[130],"investigate":[131],"multiple":[132],"architectural":[133],"variants,":[134],"including":[135],"Homogeneous":[136],"MoE,":[137,139],"Heterogeneous":[138],"Multi-Gate":[141,164],"MoE":[142,165],"(MMoE).":[143],"Performance":[144],"is":[145],"evaluated":[146],"in":[147,204],"both":[148],"standard":[149],"adversarial":[151],"settings":[152],"using":[153],"original":[154],"mutated":[156],"obtained":[159],"results":[160],"demonstrate":[161],"that":[162],"achieves":[167],"best":[169],"reaching":[171],"combined":[173],"rate":[175],"0.9744":[177],"with":[178],"only":[179],"$2.56\\%$":[180],"failure":[181],"rate.":[182],"Moreover,":[183],"configuration":[185],"exhibits":[186],"improved":[187],"robustness":[188],"under":[189],"mutation-induced":[190],"shifts.":[192],"Our":[193],"findings":[194],"highlight":[195],"effectiveness":[197],"specialization":[200],"routing":[203],"handling":[205],"complex":[206],"distributions,":[208],"making":[209],"promising":[214],"direction":[215],"for":[216],"scalable":[217],"resilient":[219],"systems.":[222]},"counts_by_year":[],"updated_date":"2026-07-01T06:29:00.853634","created_date":"2026-07-01T00:00:00"}