{"id":"https://openalex.org/W4404910489","doi":"https://doi.org/10.1145/3694811.3697818","title":"Detecting Edge and Node Anomalies with Temporal GNNs","display_name":"Detecting Edge and Node Anomalies with Temporal GNNs","publication_year":2024,"publication_date":"2024-12-02","ids":{"openalex":"https://openalex.org/W4404910489","doi":"https://doi.org/10.1145/3694811.3697818"},"language":"en","primary_location":{"id":"doi:10.1145/3694811.3697818","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3694811.3697818","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 3rd GNNet Workshop on Graph Neural Networking Workshop","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3694811.3697818","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101507980","display_name":"Andrea Cavallo","orcid":"https://orcid.org/0009-0006-1226-3926"},"institutions":[{"id":"https://openalex.org/I98358874","display_name":"Delft University of Technology","ror":"https://ror.org/02e2c7k09","country_code":"NL","type":"education","lineage":["https://openalex.org/I98358874"]}],"countries":["NL"],"is_corresponding":true,"raw_author_name":"Andrea Cavallo","raw_affiliation_strings":["Delft University of Technology, Delft, NL"],"affiliations":[{"raw_affiliation_string":"Delft University of Technology, Delft, NL","institution_ids":["https://openalex.org/I98358874"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057423096","display_name":"Luca Gioacchini","orcid":"https://orcid.org/0000-0001-8258-8626"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Politecnico di Torino","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Luca Gioacchini","raw_affiliation_strings":["Politecnico di Torino, Torino, Italy"],"affiliations":[{"raw_affiliation_string":"Politecnico di Torino, Torino, Italy","institution_ids":["https://openalex.org/I177477856"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064639744","display_name":"Luca Vassio","orcid":"https://orcid.org/0000-0002-2920-1856"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Politecnico di Torino","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Luca Vassio","raw_affiliation_strings":["DAUIN, Politecnico di Torino, Torino, Italy"],"affiliations":[{"raw_affiliation_string":"DAUIN, Politecnico di Torino, Torino, Italy","institution_ids":["https://openalex.org/I177477856"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060087704","display_name":"Marco Mellia","orcid":"https://orcid.org/0000-0003-1859-6693"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Politecnico di Torino","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Marco Mellia","raw_affiliation_strings":["Politecnico di Torino, Torino, Italy"],"affiliations":[{"raw_affiliation_string":"Politecnico di Torino, Torino, Italy","institution_ids":["https://openalex.org/I177477856"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101507980"],"corresponding_institution_ids":["https://openalex.org/I98358874"],"apc_list":null,"apc_paid":null,"fwci":0.3506,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.64004886,"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":"7","last_page":"13"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9994999766349792,"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":0.9994999766349792,"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":0.9994999766349792,"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/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.9812999963760376,"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":0.614054799079895},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.525842010974884},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.4491361379623413},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2643956243991852},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0696101188659668}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.614054799079895},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.525842010974884},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.4491361379623413},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2643956243991852},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0696101188659668},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3694811.3697818","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3694811.3697818","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 3rd GNNet Workshop on Graph Neural Networking Workshop","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3694811.3697818","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3694811.3697818","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 3rd GNNet Workshop on Graph Neural Networking Workshop","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2144182447","https://openalex.org/W2157331557","https://openalex.org/W2224609888","https://openalex.org/W2278186031","https://openalex.org/W2746170296","https://openalex.org/W2901504064","https://openalex.org/W2958285686","https://openalex.org/W2986944522","https://openalex.org/W3019863187","https://openalex.org/W3026076535","https://openalex.org/W3133518153","https://openalex.org/W3158906645","https://openalex.org/W3172408309","https://openalex.org/W3206604724","https://openalex.org/W4283745693","https://openalex.org/W4307042912","https://openalex.org/W4312512934","https://openalex.org/W4360851419","https://openalex.org/W4376480418","https://openalex.org/W4389154999"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Computer":[0],"and":[1,62,99,109,115,157,167],"social":[2,100],"networks":[3,29],"can":[4],"be":[5],"effectively":[6],"represented":[7],"as":[8,95],"complex":[9],"temporal":[10,86,123],"graphs":[11],"where":[12],"entities":[13,59],"(nodes)":[14],"keep":[15],"interconnecting":[16],"through":[17],"various":[18],"relationships":[19],"(edges),":[20],"forming":[21],"evolving":[22],"structures.":[23],"Anomaly":[24],"Detection":[25],"(AD)":[26],"in":[27,93,97,134],"such":[28],"consists":[30],"of":[31,48,68,72,106,112,173],"identifying":[32],"patterns":[33],"diverging":[34],"from":[35],"what":[36],"is":[37,43,77],"expected":[38],"or":[39,57],"normal.":[40],"This":[41,88],"task":[42],"fundamental":[44],"for":[45],"the":[46,66,75,147,153],"detection":[47],"potential":[49],"threats":[50],"--":[51],"e.g.":[52],"suspicious":[53],"connections":[54],"(edge":[55],"AD)":[56],"misbehaving":[58],"(node":[60],"AD),":[61],"challenging":[63],"due":[64],"to":[65,81,121,146],"lack":[67,105],"a":[69,135],"common":[70],"definition":[71],"anomaly.":[73],"However,":[74],"literature":[76],"scarce":[78],"about":[79],"solutions":[80],"detect":[82,164],"node":[83,166],"anomalies":[84,169],"on":[85,155],"graphs.":[87],"work":[89],"addresses":[90],"three":[91],"challenges":[92],"AD":[94,131],"found":[96],"computer":[98],"networks:":[101],"fast-evolving":[102],"graph":[103],"structure,":[104],"ground":[107],"truth,":[108],"simultaneous":[110],"presence":[111],"anomalous":[113],"nodes":[114],"edges.":[116],"For":[117],"this,":[118],"we":[119],"propose":[120],"use":[122],"Graph":[124],"Neural":[125],"Networks":[126],"(tGNNs)":[127],"coupled":[128],"with":[129],"specialised":[130],"blocks":[132],"trained":[133],"self-supervised":[136],"way.":[137],"We":[138,150],"also":[139],"embed":[140],"an":[141],"attention":[142],"mechanism":[143],"providing":[144],"interpretability":[145],"decision":[148],"process.":[149],"extensively":[151],"validate":[152],"tGNNs":[154],"synthetic":[156],"real-world":[158],"datasets":[159],"showing":[160],"that":[161],"they":[162],"successfully":[163],"both":[165],"edge":[168],"simultaneously":[170],"(around":[171],"0.9":[172],"average":[174],"AUC).":[175]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-03-27T14:29:43.386196","created_date":"2025-10-10T00:00:00"}