{"id":"https://openalex.org/W3160743305","doi":"https://doi.org/10.1109/csr51186.2021.9527927","title":"Machine learning on knowledge graphs for context-aware security monitoring","display_name":"Machine learning on knowledge graphs for context-aware security monitoring","publication_year":2021,"publication_date":"2021-07-26","ids":{"openalex":"https://openalex.org/W3160743305","doi":"https://doi.org/10.1109/csr51186.2021.9527927","mag":"3160743305"},"language":"en","primary_location":{"id":"doi:10.1109/csr51186.2021.9527927","is_oa":false,"landing_page_url":"https://doi.org/10.1109/csr51186.2021.9527927","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Cyber Security and Resilience (CSR)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2105.08741","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5048833485","display_name":"Josep Soler Garrido","orcid":"https://orcid.org/0000-0002-9669-3459"},"institutions":[{"id":"https://openalex.org/I1325886976","display_name":"Siemens (Germany)","ror":"https://ror.org/059mq0909","country_code":"DE","type":"company","lineage":["https://openalex.org/I1325886976"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Josep Soler Garrido","raw_affiliation_strings":["Siemens Technology, Munich, Germany","[Siemens Technology, Munich, Germany]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Siemens Technology, Munich, Germany","institution_ids":["https://openalex.org/I1325886976"]},{"raw_affiliation_string":"[Siemens Technology, Munich, Germany]","institution_ids":["https://openalex.org/I1325886976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063752112","display_name":"Dominik Dold","orcid":"https://orcid.org/0000-0001-7626-9960"},"institutions":[{"id":"https://openalex.org/I1325886976","display_name":"Siemens (Germany)","ror":"https://ror.org/059mq0909","country_code":"DE","type":"company","lineage":["https://openalex.org/I1325886976"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Dominik Dold","raw_affiliation_strings":["Siemens Technology, Munich, Germany","[Siemens Technology, Munich, Germany]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Siemens Technology, Munich, Germany","institution_ids":["https://openalex.org/I1325886976"]},{"raw_affiliation_string":"[Siemens Technology, Munich, Germany]","institution_ids":["https://openalex.org/I1325886976"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110840942","display_name":"Johannes Frank","orcid":null},"institutions":[{"id":"https://openalex.org/I1325886976","display_name":"Siemens (Germany)","ror":"https://ror.org/059mq0909","country_code":"DE","type":"company","lineage":["https://openalex.org/I1325886976"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Johannes Frank","raw_affiliation_strings":["Siemens Technology, Munich, Germany","Siemens;"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Siemens Technology, Munich, Germany","institution_ids":["https://openalex.org/I1325886976"]},{"raw_affiliation_string":"Siemens;","institution_ids":["https://openalex.org/I1325886976"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3207,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.59595836,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"55","last_page":"60"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9988999962806702,"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"}},"topics":[{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9988999962806702,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9976999759674072,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9962000250816345,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8013920783996582},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.7108733654022217},{"id":"https://openalex.org/keywords/intrusion-detection-system","display_name":"Intrusion detection system","score":0.684299886226654},{"id":"https://openalex.org/keywords/sophistication","display_name":"Sophistication","score":0.6360316872596741},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6082573533058167},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.5968694090843201},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5602350234985352},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.4873426854610443},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.42970722913742065},{"id":"https://openalex.org/keywords/domain-knowledge","display_name":"Domain knowledge","score":0.4251772463321686},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34097427129745483}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8013920783996582},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.7108733654022217},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.684299886226654},{"id":"https://openalex.org/C168725872","wikidata":"https://www.wikidata.org/wiki/Q991663","display_name":"Sophistication","level":2,"score":0.6360316872596741},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6082573533058167},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.5968694090843201},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5602350234985352},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.4873426854610443},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.42970722913742065},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.4251772463321686},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34097427129745483},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/csr51186.2021.9527927","is_oa":false,"landing_page_url":"https://doi.org/10.1109/csr51186.2021.9527927","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Cyber Security and Resilience (CSR)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2105.08741","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2105.08741","pdf_url":"https://arxiv.org/pdf/2105.08741","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2105.08741","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2105.08741","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":"article-journal"},{"id":"mag:3160743305","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":null}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2105.08741","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2105.08741","pdf_url":"https://arxiv.org/pdf/2105.08741","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.4099999964237213}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W205829674","https://openalex.org/W1929674166","https://openalex.org/W1993845689","https://openalex.org/W2044880677","https://openalex.org/W2089554624","https://openalex.org/W2300469216","https://openalex.org/W2466206609","https://openalex.org/W2487152776","https://openalex.org/W2640631472","https://openalex.org/W2891813744","https://openalex.org/W2892748737","https://openalex.org/W2944534303","https://openalex.org/W2963224980","https://openalex.org/W2966841471","https://openalex.org/W2980659949","https://openalex.org/W2981025625","https://openalex.org/W2990619902","https://openalex.org/W2990623250","https://openalex.org/W2990995058","https://openalex.org/W2997610263","https://openalex.org/W2997634552","https://openalex.org/W3000539293","https://openalex.org/W3009152417","https://openalex.org/W3011124515","https://openalex.org/W3017093935","https://openalex.org/W3017312168","https://openalex.org/W3094320230","https://openalex.org/W3186276894","https://openalex.org/W4238948521","https://openalex.org/W6608344535","https://openalex.org/W6661564250","https://openalex.org/W6719918161","https://openalex.org/W6762125437","https://openalex.org/W6798681010","https://openalex.org/W6802311950"],"related_works":["https://openalex.org/W3198760505","https://openalex.org/W3097165720","https://openalex.org/W3120347381","https://openalex.org/W3029189887","https://openalex.org/W3003526064","https://openalex.org/W3139301417","https://openalex.org/W2998689367","https://openalex.org/W2186776128","https://openalex.org/W2252012216","https://openalex.org/W2804949059","https://openalex.org/W3121835124","https://openalex.org/W134426264","https://openalex.org/W3168924310","https://openalex.org/W2911399349","https://openalex.org/W1488515281","https://openalex.org/W2346277511","https://openalex.org/W3152602106","https://openalex.org/W3032379897","https://openalex.org/W3045527342","https://openalex.org/W3091621850"],"abstract_inverted_index":{"Machine":[0],"learning":[1,92,142],"techniques":[2],"are":[3,56],"gaining":[4],"attention":[5],"in":[6,31,42,59,109,128],"the":[7,14,26,45,50,60,64,88,116,136],"context":[8],"of":[9,17,44,49,69,90,132,139],"intrusion":[10,97,147],"detection":[11,98,148],"due":[12],"to":[13,66,73,76,121],"increasing":[15],"amounts":[16],"data":[18,79],"generated":[19,51],"by":[20,29],"monitoring":[21],"tools,":[22],"as":[23,25],"well":[24],"sophistication":[27],"displayed":[28],"attackers":[30],"hiding":[32],"their":[33,74],"activity.":[34],"However,":[35],"existing":[36],"methods":[37],"often":[38],"exhibit":[39],"important":[40],"limitations":[41],"terms":[43],"quantity":[46],"and":[47,99,125],"relevance":[48],"alerts.":[52],"Recently,":[53],"knowledge":[54,94,144],"graphs":[55,95,145],"finding":[57],"application":[58,89],"cybersecurity":[61],"domain,":[62],"showing":[63],"potential":[65,137],"alleviate":[67],"some":[68],"these":[70],"drawbacks":[71],"thanks":[72],"ability":[75],"seamlessly":[77],"integrate":[78],"from":[80],"multiple":[81],"domains":[82],"using":[83],"human-understandable":[84],"vocabularies.":[85],"We":[86],"discuss":[87],"machine":[91,141],"on":[93,143],"for":[96,105,146],"experimentally":[100],"evaluate":[101],"a":[102,129],"link-prediction":[103],"method":[104,118],"scoring":[106],"anomalous":[107],"activity":[108],"industrial":[110],"systems.":[111],"After":[112],"initial":[113],"unsupervised":[114],"training,":[115],"proposed":[117],"is":[119],"shown":[120],"produce":[122],"intuitively":[123],"well-calibrated":[124],"interpretable":[126],"alerts":[127],"diverse":[130],"range":[131],"scenarios,":[133],"hinting":[134],"at":[135],"benefits":[138],"relational":[140],"purposes.":[149]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}