{"id":"https://openalex.org/W2535120693","doi":"https://doi.org/10.1145/2996758.2996761","title":"Discriminative Models for Multi-instance Problems with Tree Structure","display_name":"Discriminative Models for Multi-instance Problems with Tree Structure","publication_year":2016,"publication_date":"2016-10-27","ids":{"openalex":"https://openalex.org/W2535120693","doi":"https://doi.org/10.1145/2996758.2996761","mag":"2535120693"},"language":"en","primary_location":{"id":"doi:10.1145/2996758.2996761","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2996758.2996761","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2016 ACM Workshop on Artificial Intelligence and Security","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://library.utia.cas.cz/separaty/2016/RO/somol-0463379.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5059337672","display_name":"Tom\u00e1\u0161 Pevn\u00fd","orcid":"https://orcid.org/0000-0002-5768-9713"},"institutions":[{"id":"https://openalex.org/I44504214","display_name":"Czech Technical University in Prague","ror":"https://ror.org/03kqpb082","country_code":"CZ","type":"education","lineage":["https://openalex.org/I44504214"]}],"countries":["CZ"],"is_corresponding":false,"raw_author_name":"Tomas Pevny","raw_affiliation_strings":["Czech Technical University in Prague, Prague, Czech Rep"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Czech Technical University in Prague, Prague, Czech Rep","institution_ids":["https://openalex.org/I44504214"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073245119","display_name":"Petr Somol","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Petr Somol","raw_affiliation_strings":["Cisco R&D center in Prague, Prague, Czech Rep"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cisco R&D center in Prague, Prague, Czech Rep","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.1656,"has_fulltext":true,"cited_by_count":18,"citation_normalized_percentile":{"value":0.82158103,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"83","last_page":"91"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.996399998664856,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.996399998664856,"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":0.9936000108718872,"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":0.9934999942779541,"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/discriminative-model","display_name":"Discriminative model","score":0.9056174755096436},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8297667503356934},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6372653841972351},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.61234450340271},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5764572024345398},{"id":"https://openalex.org/keywords/server","display_name":"Server","score":0.5696417689323425},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4629242420196533},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.44241583347320557},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.15241894125938416}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.9056174755096436},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8297667503356934},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6372653841972351},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.61234450340271},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5764572024345398},{"id":"https://openalex.org/C93996380","wikidata":"https://www.wikidata.org/wiki/Q44127","display_name":"Server","level":2,"score":0.5696417689323425},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4629242420196533},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44241583347320557},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.15241894125938416}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/2996758.2996761","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2996758.2996761","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2016 ACM Workshop on Artificial Intelligence and Security","raw_type":"proceedings-article"},{"id":"pmh:oai:asep.lib.cas.cz:CavUnEpca/0463379","is_oa":true,"landing_page_url":"http://hdl.handle.net/11104/0263127","pdf_url":"http://library.utia.cas.cz/separaty/2016/RO/somol-0463379.pdf","source":{"id":"https://openalex.org/S7407055266","display_name":"ASEP","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferenceObject"},{"id":"pmh:oai:asep.lib.cas.cz:CavUnEpca/0507120","is_oa":true,"landing_page_url":"http://hdl.handle.net/11104/0298524","pdf_url":"http://library.utia.cas.cz/separaty/2019/RO/somol-0507120.pdf","source":{"id":"https://openalex.org/S7407055266","display_name":"ASEP","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":{"id":"pmh:oai:asep.lib.cas.cz:CavUnEpca/0463379","is_oa":true,"landing_page_url":"http://hdl.handle.net/11104/0263127","pdf_url":"http://library.utia.cas.cz/separaty/2016/RO/somol-0463379.pdf","source":{"id":"https://openalex.org/S7407055266","display_name":"ASEP","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferenceObject"},"sustainable_development_goals":[{"score":0.7099999785423279,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G5829116771","display_name":"Efficient subgraph discovery for petabyte-scale web analysis","funder_award_id":"GA15-08916S","funder_id":"https://openalex.org/F4320321006","funder_display_name":"Grantov\u00e1 Agentura \u010cesk\u00e9 Republiky"}],"funders":[{"id":"https://openalex.org/F4320321006","display_name":"Grantov\u00e1 Agentura \u010cesk\u00e9 Republiky","ror":"https://ror.org/01pv73b02"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2535120693.pdf","grobid_xml":"https://content.openalex.org/works/W2535120693.grobid-xml"},"referenced_works_count":18,"referenced_works":["https://openalex.org/W1592657892","https://openalex.org/W1929873255","https://openalex.org/W2010792435","https://openalex.org/W2029332168","https://openalex.org/W2096118443","https://openalex.org/W2108601876","https://openalex.org/W2110119381","https://openalex.org/W2117951582","https://openalex.org/W2125479168","https://openalex.org/W2136440798","https://openalex.org/W2162931300","https://openalex.org/W2166241213","https://openalex.org/W2525529746","https://openalex.org/W2543352470","https://openalex.org/W2604272474","https://openalex.org/W2963162436","https://openalex.org/W3150719513","https://openalex.org/W4232705770"],"related_works":["https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2761785940","https://openalex.org/W1482209366","https://openalex.org/W2110523656","https://openalex.org/W2521627374","https://openalex.org/W1487808658"],"abstract_inverted_index":{"Modelling":[0],"network":[1,84,92,226],"traffic":[2,81,119,136,179,209],"is":[3,16,72,133],"gaining":[4],"importance":[5],"to":[6,22,32,44,73,181,198,250],"counter":[7],"modern":[8],"security":[9],"threats":[10],"of":[11,28,37,57,69,147,170,192,216,239,259],"ever":[12],"increasing":[13],"sophistication.":[14],"It":[15],"though":[17],"surprisingly":[18],"difficult":[19],"and":[20,35,54,184,204,248],"costly":[21],"construct":[23],"reliable":[24],"classifiers":[25],"on":[26,96,115,135,190],"top":[27,191],"telemetry":[29],"data":[30,50],"due":[31],"the":[33,102,150,158,172,186,196,207,220,240],"variety":[34],"complexity":[36],"signals":[38],"that":[39,111,206,266],"no":[40],"human":[41,99],"can":[42,59,211],"manage":[43],"interpret":[45],"in":[46,101,128,178],"full.":[47],"Obtaining":[48],"training":[49,104],"with":[51,200,227,263],"sufficiently":[52],"large":[53,145],"variable":[55],"body":[56],"labels":[58,152],"thus":[60],"be":[61,212],"seen":[62],"as":[63,160,214,223],"a":[64,108,116,122,144,161,224],"prohibitive":[65],"problem.":[66],"The":[67,131,236],"goal":[68],"this":[70],"work":[71],"detect":[74],"infected":[75,164,271],"computers":[76],"by":[77,270],"observing":[78],"their":[79,264],"HTTP(S)":[80],"collected":[82,138],"from":[83,252],"sensors,":[85],"which":[86],"are":[87,154,267],"typically":[88,268],"proxy":[89],"servers":[90,183],"or":[91],"firewalls,":[93],"while":[94],"relying":[95],"only":[97,151,245],"minimal":[98],"input":[100],"model":[103,110,132,173,222],"phase.":[105],"We":[106,194,218],"propose":[107],"discriminative":[109,176,221],"makes":[112],"decisions":[113],"based":[114],"computer's":[117],"all":[118],"observed":[120],"during":[121],"predefined":[123],"time":[124,141],"window":[125],"(5":[126],"minutes":[127],"our":[129],"case).":[130],"trained":[134],"samples":[137],"over":[139],"equally-sized":[140],"windows":[142],"for":[143],"number":[146],"computers,":[148],"where":[149],"needed":[153],"(human)":[155],"verdicts":[156],"about":[157],"computer":[159],"whole":[162],"(presumed":[163],"vs.":[165],"presumed":[166],"clean).":[167],"As":[168],"part":[169],"training,":[171],"itself":[174],"learns":[175],"patterns":[177,210],"targeted":[180],"individual":[182],"constructs":[185],"final":[187],"high-level":[188],"classifier":[189,197],"them.":[193],"show":[195],"perform":[199],"very":[201],"high":[202],"precision,":[203],"demonstrate":[205],"learned":[208],"interpreted":[213],"Indicators":[215],"Compromise.":[217],"implement":[219],"neural":[225],"special":[228],"structure":[229],"reflecting":[230],"two":[231],"stacked":[232],"multi":[233],"instance":[234],"problems.":[235],"main":[237],"advantages":[238],"proposed":[241],"configuration":[242],"include":[243],"not":[244],"improved":[246],"accuracy":[247],"ability":[249],"learn":[251],"gross":[253],"labels,":[254],"but":[255],"also":[256],"automatic":[257],"learning":[258],"server":[260],"types":[261],"(together":[262],"detectors)":[265],"visited":[269],"computers.":[272]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":4},{"year":2017,"cited_by_count":2}],"updated_date":"2026-08-11T07:18:39.950985","created_date":"2025-10-10T00:00:00"}