{"id":"https://openalex.org/W4205814501","doi":"https://doi.org/10.1109/bigdata52589.2021.9672062","title":"Cybersecurity Knowledge Graph Improvement with Graph Neural Networks","display_name":"Cybersecurity Knowledge Graph Improvement with Graph Neural Networks","publication_year":2021,"publication_date":"2021-12-15","ids":{"openalex":"https://openalex.org/W4205814501","doi":"https://doi.org/10.1109/bigdata52589.2021.9672062"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata52589.2021.9672062","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata52589.2021.9672062","pdf_url":null,"source":{"id":"https://openalex.org/S4363607718","display_name":"2021 IEEE International Conference on Big Data (Big Data)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.13016/m287mm-wfql","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5075856906","display_name":"Soham Dasgupta","orcid":"https://orcid.org/0000-0002-0522-9889"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Soham Dasgupta","raw_affiliation_strings":["Mallya Aditi International School"],"affiliations":[{"raw_affiliation_string":"Mallya Aditi International School","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014855298","display_name":"Aritran Piplai","orcid":"https://orcid.org/0000-0002-6437-1324"},"institutions":[{"id":"https://openalex.org/I79272384","display_name":"University of Maryland, Baltimore County","ror":"https://ror.org/02qskvh78","country_code":"US","type":"education","lineage":["https://openalex.org/I79272384"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Aritran Piplai","raw_affiliation_strings":["Dept. of Computer Science & Electrical Engineering, University of Maryland, Baltimore County"],"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science & Electrical Engineering, University of Maryland, Baltimore County","institution_ids":["https://openalex.org/I79272384"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090051188","display_name":"Priyanka Ranade","orcid":"https://orcid.org/0000-0003-3859-5356"},"institutions":[{"id":"https://openalex.org/I79272384","display_name":"University of Maryland, Baltimore County","ror":"https://ror.org/02qskvh78","country_code":"US","type":"education","lineage":["https://openalex.org/I79272384"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Priyanka Ranade","raw_affiliation_strings":["Dept. of Computer Science & Electrical Engineering, University of Maryland, Baltimore County"],"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science & Electrical Engineering, University of Maryland, Baltimore County","institution_ids":["https://openalex.org/I79272384"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020975010","display_name":"Anupam Joshi","orcid":"https://orcid.org/0000-0002-8641-3193"},"institutions":[{"id":"https://openalex.org/I79272384","display_name":"University of Maryland, Baltimore County","ror":"https://ror.org/02qskvh78","country_code":"US","type":"education","lineage":["https://openalex.org/I79272384"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Anupam Joshi","raw_affiliation_strings":["Dept. of Computer Science & Electrical Engineering, University of Maryland, Baltimore County"],"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science & Electrical Engineering, University of Maryland, Baltimore County","institution_ids":["https://openalex.org/I79272384"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5075856906"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.754,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.75107497,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"3290","last_page":"3297"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","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/T11273","display_name":"Advanced Graph Neural Networks","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/T11719","display_name":"Data Quality and Management","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"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/T10028","display_name":"Topic Modeling","score":0.992900013923645,"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/computer-science","display_name":"Computer science","score":0.8398554921150208},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6203433275222778},{"id":"https://openalex.org/keywords/semantic-similarity","display_name":"Semantic similarity","score":0.5493563413619995},{"id":"https://openalex.org/keywords/sparql","display_name":"SPARQL","score":0.520571768283844},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5113822817802429},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5036291480064392},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.469107449054718},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4329453706741333},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.43085977435112},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.424045592546463},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.389191210269928},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.32940754294395447},{"id":"https://openalex.org/keywords/semantic-web","display_name":"Semantic Web","score":0.2968066930770874},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.26482194662094116},{"id":"https://openalex.org/keywords/rdf","display_name":"RDF","score":0.24164873361587524}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8398554921150208},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6203433275222778},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.5493563413619995},{"id":"https://openalex.org/C41009113","wikidata":"https://www.wikidata.org/wiki/Q54871","display_name":"SPARQL","level":4,"score":0.520571768283844},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5113822817802429},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5036291480064392},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.469107449054718},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4329453706741333},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.43085977435112},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.424045592546463},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.389191210269928},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.32940754294395447},{"id":"https://openalex.org/C2129575","wikidata":"https://www.wikidata.org/wiki/Q54837","display_name":"Semantic Web","level":2,"score":0.2968066930770874},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.26482194662094116},{"id":"https://openalex.org/C147497476","wikidata":"https://www.wikidata.org/wiki/Q54872","display_name":"RDF","level":3,"score":0.24164873361587524},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/bigdata52589.2021.9672062","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata52589.2021.9672062","pdf_url":null,"source":{"id":"https://openalex.org/S4363607718","display_name":"2021 IEEE International Conference on Big Data (Big Data)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},{"id":"pmh:oai:mdsoar.org:11603/24127","is_oa":false,"landing_page_url":"http://hdl.handle.net/11603/24127","pdf_url":null,"source":{"id":"https://openalex.org/S4306402556","display_name":"Maryland Shared Open Access Repository (USMAI Consortium)","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Text"},{"id":"doi:10.13016/m287mm-wfql","is_oa":true,"landing_page_url":"https://doi.org/10.13016/m287mm-wfql","pdf_url":null,"source":{"id":"https://openalex.org/S4306402644","display_name":"Digital Repository at the University of Maryland (University of Maryland College Park)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I66946132","host_organization_name":"University of Maryland, College Park","host_organization_lineage":["https://openalex.org/I66946132"],"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"}],"best_oa_location":{"id":"doi:10.13016/m287mm-wfql","is_oa":true,"landing_page_url":"https://doi.org/10.13016/m287mm-wfql","pdf_url":null,"source":{"id":"https://openalex.org/S4306402644","display_name":"Digital Repository at the University of Maryland (University of Maryland College Park)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I66946132","host_organization_name":"University of Maryland, College Park","host_organization_lineage":["https://openalex.org/I66946132"],"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":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W1513231349","https://openalex.org/W1662382123","https://openalex.org/W2007562169","https://openalex.org/W2134063365","https://openalex.org/W2151298633","https://openalex.org/W2487152776","https://openalex.org/W2610153490","https://openalex.org/W2624407581","https://openalex.org/W2753718471","https://openalex.org/W2807021761","https://openalex.org/W2893671662","https://openalex.org/W2945298546","https://openalex.org/W2963911286","https://openalex.org/W2963921057","https://openalex.org/W2964015378","https://openalex.org/W2964113829","https://openalex.org/W2964321699","https://openalex.org/W2993623323","https://openalex.org/W2996800219","https://openalex.org/W2997634552","https://openalex.org/W3000539293","https://openalex.org/W3007913393","https://openalex.org/W3100848837","https://openalex.org/W3110206688","https://openalex.org/W3111854523","https://openalex.org/W3112693483","https://openalex.org/W3163378277","https://openalex.org/W3179788886","https://openalex.org/W3198980504","https://openalex.org/W4239319433","https://openalex.org/W4294558607","https://openalex.org/W4297782361","https://openalex.org/W4394663333","https://openalex.org/W6630632610","https://openalex.org/W6637178625","https://openalex.org/W6661564250","https://openalex.org/W6679728604","https://openalex.org/W6685350579","https://openalex.org/W6720006811","https://openalex.org/W6726873649","https://openalex.org/W6737558694","https://openalex.org/W6738964360","https://openalex.org/W6744241167","https://openalex.org/W6758183469","https://openalex.org/W6762125437","https://openalex.org/W6763051974"],"related_works":["https://openalex.org/W2038821533","https://openalex.org/W1993638553","https://openalex.org/W2295889387","https://openalex.org/W76044956","https://openalex.org/W129667569","https://openalex.org/W3142934089","https://openalex.org/W2528665947","https://openalex.org/W2764264137","https://openalex.org/W2226235235","https://openalex.org/W64303689"],"abstract_inverted_index":{"Cybersecurity":[0],"Knowledge":[1],"Graphs":[2],"(CKGs)":[3],"help":[4,101],"in":[5,33,45,51,78,114,138,153],"aggregating":[6],"information":[7,26,76,112],"about":[8,27],"cyber-events.":[9],"CKGs":[10,48,179],"combined":[11],"with":[12,40,133],"reasoning":[13],"and":[14,65],"querying":[15],"systems":[16],"such":[17],"as":[18],"SPARQL":[19],"enable":[20],"security":[21],"researchers":[22],"to":[23,184],"look":[24],"up":[25],"past":[28],"cyberevents":[29],"that":[30,99,129,148,159,180],"is":[31,117],"helpful":[32],"understanding":[34],"future":[35],"cyber-events":[36],"or":[37],"drawing":[38],"similarity":[39],"a":[41,46,60,63,97,118,126,131,154,176],"known":[42],"cyber-event":[43],"recorded":[44],"CKG.":[47],"have":[49,90],"assertions":[50],"the":[52,79,83,104,107,111,115,134,139,161,186],"form":[53],"of":[54,68,75,93,106,178],"semantic":[55,135,146,190],"triples.":[56],"The":[57,73],"triples":[58,136,147],"describe":[59,125],"relationship":[61],"between":[62],"subject":[64],"object,":[66],"both":[67],"which":[69],"are":[70,151],"cybersecurity":[71],"entities.":[72],"quality":[74],"present":[77],"CKG":[80,108,116,140],"depends":[81],"on":[82,175],"data":[84,87],"source.":[85],"Since":[86],"sources":[88],"can":[89,181],"varying":[91],"degrees":[92],"reliability,":[94],"we":[95,124,149,168],"need":[96],"score":[98,132],"should":[100],"us":[102],"benchmark":[103],"veracity":[105],"assertions.":[109],"Verifying":[110],"asserted":[113,137],"challenging":[119],"task.":[120],"In":[121,166],"this":[122],"paper,":[123],"novel":[127],"method":[128],"associates":[130],"using":[141],"deep":[142],"learning.":[143],"We":[144],"use":[145,169],"know":[150],"correct,":[152],"supervised":[155],"machine":[156],"learning":[157],"algorithm":[158],"produces":[160],"output":[162],"for":[163,188],"each":[164,189],"relationship.":[165],"particular,":[167],"Graph":[170],"Convolutional":[171],"Neural":[172],"Networks":[173],"(GCN)":[174],"dataset":[177],"be":[182],"used":[183],"ascertain":[185],"scores":[187],"triple.":[191]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
