{"id":"https://openalex.org/W7152980456","doi":"https://doi.org/10.48550/arxiv.2604.08140","title":"Multimodal Reasoning with LLM for Encrypted Traffic Interpretation: A Benchmark","display_name":"Multimodal Reasoning with LLM for Encrypted Traffic Interpretation: A Benchmark","publication_year":2026,"publication_date":"2026-04-09","ids":{"openalex":"https://openalex.org/W7152980456","doi":"https://doi.org/10.48550/arxiv.2604.08140"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.08140","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.08140","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.2604.08140","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133346737","display_name":"Longgang Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Longgang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132554459","display_name":"Xiaowei Fu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fu, Xiaowei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132665940","display_name":"Fuxiang Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Fuxiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5133352206","display_name":"Lei Zhang","orcid":"https://orcid.org/0000-0003-2343-084X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Lei","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/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.9901999831199646,"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/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.9901999831199646,"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":0.002199999988079071,"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/T14258","display_name":"Legal and Policy Issues","score":0.0006000000284984708,"subfield":{"id":"https://openalex.org/subfields/3308","display_name":"Law"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.536899983882904},{"id":"https://openalex.org/keywords/encryption","display_name":"Encryption","score":0.49390000104904175},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.4805000126361847},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.423799991607666},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.37880000472068787},{"id":"https://openalex.org/keywords/byte","display_name":"Byte","score":0.32679998874664307},{"id":"https://openalex.org/keywords/case-based-reasoning","display_name":"Case-based reasoning","score":0.32199999690055847},{"id":"https://openalex.org/keywords/source-code","display_name":"Source code","score":0.3043000102043152}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7886000275611877},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.536899983882904},{"id":"https://openalex.org/C148730421","wikidata":"https://www.wikidata.org/wiki/Q141090","display_name":"Encryption","level":2,"score":0.49390000104904175},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.4805000126361847},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4787999987602234},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.423799991607666},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4156999886035919},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.37880000472068787},{"id":"https://openalex.org/C43364308","wikidata":"https://www.wikidata.org/wiki/Q8799","display_name":"Byte","level":2,"score":0.32679998874664307},{"id":"https://openalex.org/C20162079","wikidata":"https://www.wikidata.org/wiki/Q1151406","display_name":"Case-based reasoning","level":2,"score":0.32199999690055847},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.3043000102043152},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.30309998989105225},{"id":"https://openalex.org/C92717368","wikidata":"https://www.wikidata.org/wiki/Q1162538","display_name":"Plaintext","level":3,"score":0.295199990272522},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.29269999265670776},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.2913999855518341},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2888000011444092},{"id":"https://openalex.org/C9616225","wikidata":"https://www.wikidata.org/wiki/Q3929429","display_name":"Semantic reasoner","level":2,"score":0.2856999933719635},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.2797999978065491},{"id":"https://openalex.org/C161301231","wikidata":"https://www.wikidata.org/wiki/Q3478658","display_name":"Knowledge representation and reasoning","level":2,"score":0.27970001101493835},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.2750000059604645},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.265500009059906},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.25920000672340393},{"id":"https://openalex.org/C37335422","wikidata":"https://www.wikidata.org/wiki/Q6888134","display_name":"Model-based reasoning","level":3,"score":0.2540999948978424},{"id":"https://openalex.org/C89288958","wikidata":"https://www.wikidata.org/wiki/Q7301504","display_name":"Reasoning system","level":2,"score":0.25029999017715454}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.08140","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.08140","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.2604.08140","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.08140","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":[{"score":0.6424551010131836,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Network":[0],"traffic,":[1],"as":[2],"a":[3,57,89,136,158,164,169],"key":[4,27,58],"media":[5],"format,":[6],"is":[7,212],"crucial":[8],"for":[9,68,95,116],"ensuring":[10],"security":[11],"and":[12,70,111,144,153,168,191],"communications":[13],"in":[14],"modern":[15],"internet":[16],"infrastructure.":[17],"While":[18],"existing":[19,61],"methods":[20],"offer":[21],"excellent":[22],"performance,":[23],"they":[24],"face":[25],"two":[26],"bottlenecks:":[28],"(1)":[29],"They":[30],"fail":[31],"to":[32,77,149,203],"capture":[33],"multidimensional":[34],"semantics":[35],"beyond":[36],"unimodal":[37,205],"sequence":[38],"patterns.":[39],"(2)":[40],"Their":[41],"black":[42],"box":[43],"property,":[44],"i.e.,":[45],"providing":[46],"only":[47],"category":[48,180],"labels,":[49],"lacks":[50],"an":[51,130],"auditable":[52],"reasoning":[53,118,138],"process.":[54],"We":[55],"identify":[56],"factor":[59],"that":[60,185],"network":[62],"traffic":[63,122,142,166,176,193],"datasets":[64],"are":[65],"primarily":[66],"designed":[67],"classification":[69,200],"inherently":[71],"lack":[72],"rich":[73],"semantic":[74,145],"annotations,":[75],"failing":[76],"generate":[78],"human-readable":[79],"evidence":[80,115],"report.":[81],"To":[82],"address":[83],"data":[84],"scarcity,":[85],"this":[86,127],"paper":[87,128],"proposes":[88,129],"Byte-Grounded":[90],"Traffic":[91],"Description":[92],"(BGTD)":[93],"benchmark":[94],"the":[96],"first":[97],"time,":[98],"combining":[99],"raw":[100],"bytes":[101],"with":[102,178],"structured":[103],"expert":[104],"annotations.":[105],"BGTD":[106],"provides":[107],"necessary":[108],"behavioral":[109],"features":[110],"verifiable":[112],"chains":[113],"of":[114],"multimodal":[117,137],"towards":[119],"explainable":[120],"encrypted":[121],"interpretation.":[123,146],"Built":[124],"upon":[125],"BGTD,":[126],"end-to-end":[131],"traffic-language":[132],"representation":[133],"framework":[134],"(mmTraffic),":[135],"architecture":[139],"bridging":[140],"physical":[141],"encoding":[143],"In":[147],"order":[148],"alleviate":[150],"modality":[151],"interference":[152],"generative":[154],"hallucinations,":[155],"mmTraffic":[156,173,186],"adopts":[157],"jointly-optimized":[159],"perception-cognition":[160],"architecture.":[161],"By":[162],"incorporating":[163],"perception-centered":[165],"encoder":[167],"cognition-centered":[170],"LLM":[171],"generator,":[172],"achieves":[174],"refined":[175],"interpretation":[177,194],"guaranteed":[179],"prediction.":[181],"Extensive":[182],"experiments":[183],"demonstrate":[184],"autonomously":[187],"generates":[188],"high-fidelity,":[189],"human-readable,":[190],"evidence-grounded":[192],"reports,":[195],"while":[196],"maintaining":[197],"highly":[198],"competitive":[199],"accuracy":[201],"comparing":[202],"specialized":[204],"model":[206],"(e.g.,":[207],"NetMamba).":[208],"The":[209],"source":[210],"code":[211],"available":[213],"at":[214],"https://github.com/lgzhangzlg/Multimodal-Reasoning-with-LLM-for-Encrypted-Traffic-Interpretation-A-Benchmark":[215]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-11T00:00:00"}
