{"id":"https://openalex.org/W4416750780","doi":"https://doi.org/10.1109/nca67271.2025.00028","title":"ProvSpider: A Robust and Universal Toolkit for Binary Provenance Analysis Using Deep Learning","display_name":"ProvSpider: A Robust and Universal Toolkit for Binary Provenance Analysis Using Deep Learning","publication_year":2025,"publication_date":"2025-11-05","ids":{"openalex":"https://openalex.org/W4416750780","doi":"https://doi.org/10.1109/nca67271.2025.00028"},"language":null,"primary_location":{"id":"doi:10.1109/nca67271.2025.00028","is_oa":false,"landing_page_url":"https://doi.org/10.1109/nca67271.2025.00028","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 23rd International Symposium on Network Computing and Applications (NCA)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5008001911","display_name":"Zhiwei Fu","orcid":"https://orcid.org/0000-0002-2763-6186"},"institutions":[{"id":"https://openalex.org/I5023651","display_name":"McGill University","ror":"https://ror.org/01pxwe438","country_code":"CA","type":"education","lineage":["https://openalex.org/I5023651"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Zhiwei Fu","raw_affiliation_strings":["McGill University,School of Information Studies,Montreal,Quebec,Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"McGill University,School of Information Studies,Montreal,Quebec,Canada","institution_ids":["https://openalex.org/I5023651"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103067319","display_name":"Hanbo Yu","orcid":"https://orcid.org/0000-0002-6680-7240"},"institutions":[{"id":"https://openalex.org/I5023651","display_name":"McGill University","ror":"https://ror.org/01pxwe438","country_code":"CA","type":"education","lineage":["https://openalex.org/I5023651"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Hanbo Yu","raw_affiliation_strings":["McGill University,School of Information Studies,Montreal,Quebec,Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"McGill University,School of Information Studies,Montreal,Quebec,Canada","institution_ids":["https://openalex.org/I5023651"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069542066","display_name":"Xinyu Hu","orcid":"https://orcid.org/0000-0002-9739-5613"},"institutions":[{"id":"https://openalex.org/I5023651","display_name":"McGill University","ror":"https://ror.org/01pxwe438","country_code":"CA","type":"education","lineage":["https://openalex.org/I5023651"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Xinyu Hu","raw_affiliation_strings":["McGill University,School of Information Studies,Montreal,Quebec,Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"McGill University,School of Information Studies,Montreal,Quebec,Canada","institution_ids":["https://openalex.org/I5023651"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030751350","display_name":"H. H. Steven Ding","orcid":null},"institutions":[{"id":"https://openalex.org/I5023651","display_name":"McGill University","ror":"https://ror.org/01pxwe438","country_code":"CA","type":"education","lineage":["https://openalex.org/I5023651"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"H. H. Steven Ding","raw_affiliation_strings":["McGill University,School of Information Studies,Montreal,Quebec,Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"McGill University,School of Information Studies,Montreal,Quebec,Canada","institution_ids":["https://openalex.org/I5023651"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084562071","display_name":"Furkan Alaca","orcid":"https://orcid.org/0000-0002-5709-7611"},"institutions":[{"id":"https://openalex.org/I204722609","display_name":"Queen's University","ror":"https://ror.org/02y72wh86","country_code":"CA","type":"education","lineage":["https://openalex.org/I204722609"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Furkan Alaca","raw_affiliation_strings":["Queen&#x2019;s University,School of Computing,Kingston,Ontario,Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Queen&#x2019;s University,School of Computing,Kingston,Ontario,Canada","institution_ids":["https://openalex.org/I204722609"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052958340","display_name":"Philippe Charland","orcid":"https://orcid.org/0000-0003-4051-9942"},"institutions":[{"id":"https://openalex.org/I1297460800","display_name":"Defence Research and Development Canada","ror":"https://ror.org/00hgy8d33","country_code":"CA","type":"government","lineage":["https://openalex.org/I1297460800","https://openalex.org/I1336338359","https://openalex.org/I2802286613"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Philippe Charland","raw_affiliation_strings":["Mission Critical Cyber Security Section, Defence R&#x0026;D Canada - Valcartier,Quebec,QC,Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Mission Critical Cyber Security Section, Defence R&#x0026;D Canada - Valcartier,Quebec,QC,Canada","institution_ids":["https://openalex.org/I1297460800"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"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":"103","last_page":"110"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11986","display_name":"Scientific Computing and Data Management","score":0.9103999733924866,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11986","display_name":"Scientific Computing and Data Management","score":0.9103999733924866,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.043800000101327896,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"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/T10015","display_name":"Genomics and Phylogenetic Studies","score":0.005799999926239252,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/byte","display_name":"Byte","score":0.7324000000953674},{"id":"https://openalex.org/keywords/executable","display_name":"Executable","score":0.7240999937057495},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.5647000074386597},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5371000170707703},{"id":"https://openalex.org/keywords/source-code","display_name":"Source code","score":0.5127000212669373},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5016000270843506},{"id":"https://openalex.org/keywords/sliding-window-protocol","display_name":"Sliding window protocol","score":0.48159998655319214},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4659000039100647},{"id":"https://openalex.org/keywords/reverse-engineering","display_name":"Reverse engineering","score":0.3849000036716461}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8252999782562256},{"id":"https://openalex.org/C43364308","wikidata":"https://www.wikidata.org/wiki/Q8799","display_name":"Byte","level":2,"score":0.7324000000953674},{"id":"https://openalex.org/C160145156","wikidata":"https://www.wikidata.org/wiki/Q778586","display_name":"Executable","level":2,"score":0.7240999937057495},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.5647000074386597},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5371000170707703},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5239999890327454},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.5127000212669373},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5016000270843506},{"id":"https://openalex.org/C102392041","wikidata":"https://www.wikidata.org/wiki/Q592860","display_name":"Sliding window protocol","level":3,"score":0.48159998655319214},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4659000039100647},{"id":"https://openalex.org/C207850805","wikidata":"https://www.wikidata.org/wiki/Q269608","display_name":"Reverse engineering","level":2,"score":0.3849000036716461},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.34700000286102295},{"id":"https://openalex.org/C2778971978","wikidata":"https://www.wikidata.org/wiki/Q2287075","display_name":"Binary translation","level":3,"score":0.3456000089645386},{"id":"https://openalex.org/C63435697","wikidata":"https://www.wikidata.org/wiki/Q864135","display_name":"Binary code","level":3,"score":0.34380000829696655},{"id":"https://openalex.org/C2777561058","wikidata":"https://www.wikidata.org/wiki/Q2652119","display_name":"Program comprehension","level":4,"score":0.3303999900817871},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.32839998602867126},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.32440000772476196},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.31690001487731934},{"id":"https://openalex.org/C157899210","wikidata":"https://www.wikidata.org/wiki/Q1395022","display_name":"Convolutional code","level":3,"score":0.30169999599456787},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.29660001397132874},{"id":"https://openalex.org/C2781251061","wikidata":"https://www.wikidata.org/wiki/Q5416089","display_name":"Evasion (ethics)","level":3,"score":0.2922999858856201},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.29100000858306885},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.28870001435279846},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2867000102996826},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.28299999237060547},{"id":"https://openalex.org/C2778751112","wikidata":"https://www.wikidata.org/wiki/Q835016","display_name":"Window (computing)","level":2,"score":0.2799000144004822},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.27230000495910645},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.26190000772476196},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.2565999925136566},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2540999948978424}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/nca67271.2025.00028","is_oa":false,"landing_page_url":"https://doi.org/10.1109/nca67271.2025.00028","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 23rd International Symposium on Network Computing and Applications (NCA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W17195072","https://openalex.org/W1893133781","https://openalex.org/W2158698691","https://openalex.org/W2620895032","https://openalex.org/W2782780792","https://openalex.org/W2792450155","https://openalex.org/W2926178846","https://openalex.org/W2961099251","https://openalex.org/W2962802821","https://openalex.org/W2967278435","https://openalex.org/W3181292541","https://openalex.org/W4381744265","https://openalex.org/W4383221378","https://openalex.org/W4393207769","https://openalex.org/W4402347032","https://openalex.org/W4403524384"],"related_works":[],"abstract_inverted_index":{"Binary":[0],"provenance":[1,24,189],"analysis":[2,82,168,196],"recovers":[3],"essential":[4],"information,":[5],"such":[6],"as":[7,93,95],"architecture,":[8],"structure,":[9],"and":[10,53,61,69,80,100,142,179,197],"toolchain,":[11],"from":[12,26],"executables":[13],"lacking":[14],"reliable":[15],"metadata.":[16],"This":[17],"is":[18,28,107],"crucial":[19],"for":[20,186],"reverse":[21,198],"engineering.":[22,199],"However,":[23],"recovery":[25],"binaries":[27,37],"highly":[29],"challenging,":[30],"due":[31],"to":[32,86,116,128],"three":[33],"key":[34],"factors:":[35],"(1)":[36],"span":[38],"diverse":[39],"CPU":[40,97],"architectures;":[41],"(2)":[42],"Raw":[43],"byte":[44,123,154],"sequences":[45,124,155],"are":[46],"often":[47],"extremely":[48],"long":[49],"without":[50],"clear":[51],"boundaries;":[52],"(3)":[54],"Compilation":[55],"alters":[56],"control":[57],"flow,":[58],"register":[59],"usage,":[60],"memory":[62],"layout,":[63],"obscuring":[64],"the":[65,149,172,184],"original":[66],"code":[67],"structure":[68],"complicating":[70],"analysis.":[71],"To":[72],"address":[73],"these":[74],"challenges,":[75],"we":[76],"propose":[77],"a":[78,111,177],"novel":[79],"robust":[81,180],"toolset,":[83],"namely":[84],"ProvSpider,":[85],"identify":[87],"segment":[88],"boundaries,":[89],"types":[90],"of":[91],"segments":[92],"well":[94],"target":[96],"architectures,":[98],"bitness,":[99],"endianness":[101],"based":[102,109],"on":[103,110],"code-only":[104],"sections.":[105],"ProvSpider":[106,182],"built":[108],"convolutional":[112,137],"neural":[113],"network":[114],"(CNN)":[115],"learn":[117],"local":[118],"execution":[119],"patterns.":[120],"We":[121],"embed":[122],"into":[125,156],"eight-dimensional":[126],"vectors":[127],"capture":[129],"bytes\u2019":[130],"global":[131],"dependencies.":[132],"The":[133],"gating":[134],"mechanism":[135],"after":[136],"layers":[138],"filters":[139],"out":[140],"noise":[141],"keeps":[143],"most":[144],"representative":[145],"features.":[146],"At":[147],"last,":[148],"sliding":[150],"window":[151],"divides":[152],"lengthy":[153],"fixedlength":[157],"processable":[158],"chunks.":[159],"Our":[160],"model":[161],"achieves":[162],"high":[163],"accuracy":[164],"in":[165,194],"all":[166],"five":[167],"tasks,":[169],"significantly":[170],"outperforming":[171],"state-of-the-art":[173],"models.":[174],"By":[175],"providing":[176],"universal":[178],"approach,":[181],"lays":[183],"foundation":[185],"advancing":[187],"binary":[188,195],"analysis,":[190],"facilitating":[191],"future":[192],"improvements":[193]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-11-28T00:00:00"}
