{"id":"https://openalex.org/W3110210891","doi":"https://doi.org/10.1007/s10994-021-06068-6","title":"Embedding and extraction of knowledge in tree ensemble classifiers","display_name":"Embedding and extraction of knowledge in tree ensemble classifiers","publication_year":2021,"publication_date":"2021-11-24","ids":{"openalex":"https://openalex.org/W3110210891","doi":"https://doi.org/10.1007/s10994-021-06068-6","mag":"3110210891"},"language":"en","primary_location":{"id":"doi:10.1007/s10994-021-06068-6","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10994-021-06068-6","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10994-021-06068-6.pdf","source":{"id":"https://openalex.org/S62148650","display_name":"Machine Learning","issn_l":"0885-6125","issn":["0885-6125","1573-0565"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s10994-021-06068-6.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100352892","display_name":"Wei Huang","orcid":"https://orcid.org/0000-0003-1418-6267"},"institutions":[{"id":"https://openalex.org/I146655781","display_name":"University of Liverpool","ror":"https://ror.org/04xs57h96","country_code":"GB","type":"education","lineage":["https://openalex.org/I146655781"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Wei Huang","raw_affiliation_strings":["Department of Computer Science, University of Liverpool, Liverpool, UK","university of liverpool"],"raw_orcid":"https://orcid.org/0000-0003-1418-6267","affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Liverpool, Liverpool, UK","institution_ids":["https://openalex.org/I146655781"]},{"raw_affiliation_string":"university of liverpool","institution_ids":["https://openalex.org/I146655781"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100635681","display_name":"Xingyu Zhao","orcid":"https://orcid.org/0000-0002-3474-349X"},"institutions":[{"id":"https://openalex.org/I146655781","display_name":"University of Liverpool","ror":"https://ror.org/04xs57h96","country_code":"GB","type":"education","lineage":["https://openalex.org/I146655781"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Xingyu Zhao","raw_affiliation_strings":["Department of Computer Science, University of Liverpool, Liverpool, UK","university of liverpool"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Liverpool, Liverpool, UK","institution_ids":["https://openalex.org/I146655781"]},{"raw_affiliation_string":"university of liverpool","institution_ids":["https://openalex.org/I146655781"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020085889","display_name":"Xiaowei Huang","orcid":"https://orcid.org/0000-0001-6267-0366"},"institutions":[{"id":"https://openalex.org/I146655781","display_name":"University of Liverpool","ror":"https://ror.org/04xs57h96","country_code":"GB","type":"education","lineage":["https://openalex.org/I146655781"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Xiaowei Huang","raw_affiliation_strings":["Department of Computer Science, University of Liverpool, Liverpool, UK","university of liverpool"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Liverpool, Liverpool, UK","institution_ids":["https://openalex.org/I146655781"]},{"raw_affiliation_string":"university of liverpool","institution_ids":["https://openalex.org/I146655781"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5020085889","https://openalex.org/A5100352892","https://openalex.org/A5100635681"],"corresponding_institution_ids":["https://openalex.org/I146655781"],"apc_list":{"value":2990,"currency":"USD","value_usd":2990},"apc_paid":{"value":2990,"currency":"USD","value_usd":2990},"fwci":0.1302,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.53835425,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"111","issue":"5","first_page":"1925","last_page":"1958"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9998999834060669,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9998999834060669,"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/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9965000152587891,"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":0.9952999949455261,"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/backdoor","display_name":"Backdoor","score":0.8307920694351196},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.7704159021377563},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6821990013122559},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5069730281829834},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4812038242816925},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.464999794960022},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46290668845176697},{"id":"https://openalex.org/keywords/satisfiability-modulo-theories","display_name":"Satisfiability modulo theories","score":0.4503527879714966},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3693344295024872},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.10728088021278381}],"concepts":[{"id":"https://openalex.org/C2781045450","wikidata":"https://www.wikidata.org/wiki/Q254569","display_name":"Backdoor","level":2,"score":0.8307920694351196},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.7704159021377563},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6821990013122559},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5069730281829834},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4812038242816925},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.464999794960022},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46290668845176697},{"id":"https://openalex.org/C164155591","wikidata":"https://www.wikidata.org/wiki/Q2067766","display_name":"Satisfiability modulo theories","level":2,"score":0.4503527879714966},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3693344295024872},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.10728088021278381}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1007/s10994-021-06068-6","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10994-021-06068-6","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10994-021-06068-6.pdf","source":{"id":"https://openalex.org/S62148650","display_name":"Machine Learning","issn_l":"0885-6125","issn":["0885-6125","1573-0565"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2010.08281","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2010.08281","pdf_url":"https://arxiv.org/pdf/2010.08281","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:3110210891","is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2010.08281","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"pmh:oai:wrap.warwick.ac.uk:182004","is_oa":false,"landing_page_url":"https://wrap.warwick.ac.uk/182004/","pdf_url":null,"source":{"id":"https://openalex.org/S4306400665","display_name":"Warwick Research Archive Portal (University of Warwick)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I39555362","host_organization_name":"University of Warwick","host_organization_lineage":["https://openalex.org/I39555362"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Journal Article"},{"id":"doi:10.48550/arxiv.2010.08281","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2010.08281","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"article-journal"}],"best_oa_location":{"id":"doi:10.1007/s10994-021-06068-6","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10994-021-06068-6","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10994-021-06068-6.pdf","source":{"id":"https://openalex.org/S62148650","display_name":"Machine Learning","issn_l":"0885-6125","issn":["0885-6125","1573-0565"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.6800000071525574,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G7329227181","display_name":null,"funder_award_id":"956123","funder_id":"https://openalex.org/F4320335254","funder_display_name":"Horizon 2020"},{"id":"https://openalex.org/G849311619","display_name":null,"funder_award_id":"EP/T026995/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"},{"id":"https://openalex.org/F4320335254","display_name":"Horizon 2020","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3110210891.pdf","grobid_xml":"https://content.openalex.org/works/W3110210891.grobid-xml"},"referenced_works_count":45,"referenced_works":["https://openalex.org/W1748932423","https://openalex.org/W2042204882","https://openalex.org/W2060375854","https://openalex.org/W2113242816","https://openalex.org/W2153635508","https://openalex.org/W2167370496","https://openalex.org/W2275975620","https://openalex.org/W2604242010","https://openalex.org/W2748789698","https://openalex.org/W2753783305","https://openalex.org/W2772825438","https://openalex.org/W2774423163","https://openalex.org/W2788730650","https://openalex.org/W2796004214","https://openalex.org/W2803414046","https://openalex.org/W2807363941","https://openalex.org/W2900018096","https://openalex.org/W2902560707","https://openalex.org/W2934487731","https://openalex.org/W2942091739","https://openalex.org/W2942347321","https://openalex.org/W2957144537","https://openalex.org/W2962777143","https://openalex.org/W2963343288","https://openalex.org/W2963402000","https://openalex.org/W2963463132","https://openalex.org/W2963629198","https://openalex.org/W2963793947","https://openalex.org/W2964153729","https://openalex.org/W2970200861","https://openalex.org/W2971223760","https://openalex.org/W2974383344","https://openalex.org/W2982977353","https://openalex.org/W2987678574","https://openalex.org/W2990347604","https://openalex.org/W2996061416","https://openalex.org/W2997425368","https://openalex.org/W3012300836","https://openalex.org/W3015815227","https://openalex.org/W3037471945","https://openalex.org/W3120740533","https://openalex.org/W4252979261","https://openalex.org/W6637162671","https://openalex.org/W6780154528","https://openalex.org/W6788247690"],"related_works":["https://openalex.org/W2905301836","https://openalex.org/W3093516591","https://openalex.org/W3125679694","https://openalex.org/W2927299114","https://openalex.org/W3125213333","https://openalex.org/W3086146226","https://openalex.org/W2902901209","https://openalex.org/W3037085720","https://openalex.org/W3015424723","https://openalex.org/W3089068829","https://openalex.org/W3164936723","https://openalex.org/W2969466821","https://openalex.org/W3117956433","https://openalex.org/W2803678876","https://openalex.org/W2896112153","https://openalex.org/W3196119265","https://openalex.org/W2948681833","https://openalex.org/W3012469643","https://openalex.org/W2920835217","https://openalex.org/W2810818034"],"abstract_inverted_index":{"Abstract":[0],"The":[1,138],"embedding":[2,36,56,109,123,139,190],"and":[3,37,49,57,65,80,106,121,132,194,210],"extraction":[4,38,58,195],"of":[5,28,39,59,74,95,126,226],"knowledge":[6,41,60,68,102],"is":[7,87,98,128],"a":[8,71,201,223],"recent":[9],"trend":[10],"in":[11,32,61,143],"machine":[12,29],"learning":[13,30],"applications,":[14,34],"e.g.,":[15,77],"to":[16,44,89,153,162,183,222,228],"supplement":[17],"training":[18],"datasets":[19,227],"that":[20],"are":[21,42],"small.":[22],"Whilst,":[23],"as":[24,191,196],"the":[25,35,45,55,84,96,133,147,155,160,180,208],"increasing":[26],"use":[27],"models":[31],"security-critical":[33],"malicious":[40],"equivalent":[43],"notorious":[46],"backdoor":[47,81,192],"attack":[48,209],"defence,":[50,197],"respectively.":[51],"This":[52],"paper":[53],"studies":[54],"tree":[62,215],"ensemble":[63,216],"classifiers,":[64],"focuses":[66],"on":[67],"expressible":[69],"with":[70,165,214],"generic":[72],"form":[73],"Boolean":[75],"formulas,":[76],"point-wise":[78],"robustness":[79],"attacks.":[82],"For":[83],"embedding,":[85,148],"it":[86],"required":[88],"be":[90,104,111,141,163],"preservative":[91],"(the":[92,101,108],"original":[93],"performance":[94],"classifier":[97],"preserved),":[99],"verifiable":[100],"can":[103,140,176],"attested),":[105],"stealthy":[107],"cannot":[110],"easily":[112],"detected).":[113],"To":[114],"facilitate":[115],"this,":[116],"we":[117,149],"propose":[118],"two":[119],"novel,":[120],"effective":[122],"algorithms,":[124],"one":[125],"which":[127],"for":[129,135],"black-box":[130],"settings":[131],"other":[134],"white-box":[136],"settings.":[137],"done":[142],"PTIME":[144],".":[145],"Beyond":[146],"develop":[150],"an":[151,166,184],"algorithm":[152,175],"extract":[154,178],"embedded":[156],"knowledge,":[157,179],"by":[158],"reducing":[159],"problem":[161],"solvable":[164],"SMT":[167],"(satisfiability":[168],"modulo":[169],"theories)":[170],"solver.":[171],"While":[172],"this":[173],"novel":[174],"successfully":[177],"reduction":[181],"leads":[182],"NP":[185],"computation.":[186],"Therefore,":[187],"if":[188],"applying":[189],"attacks":[193],"our":[198,220,230],"results":[199],"suggest":[200],"complexity":[202],"gap":[203],"(P":[204],"vs.":[205],"NP)":[206],"between":[207],"defence":[211],"when":[212],"working":[213],"classifiers.":[217],"We":[218],"apply":[219],"algorithms":[221],"diverse":[224],"set":[225],"validate":[229],"conclusion":[231],"extensively.":[232]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-31T08:31:51.225901","created_date":"2025-10-10T00:00:00"}
