{"id":"https://openalex.org/W2963190580","doi":"https://doi.org/10.1109/icassp.2016.7472539","title":"Multi-centrality graph spectral decompositions and their application to cyber intrusion detection","display_name":"Multi-centrality graph spectral decompositions and their application to cyber intrusion detection","publication_year":2016,"publication_date":"2016-03-01","ids":{"openalex":"https://openalex.org/W2963190580","doi":"https://doi.org/10.1109/icassp.2016.7472539","mag":"2963190580"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2016.7472539","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2016.7472539","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5050344371","display_name":"Pin\u2010Yu Chen","orcid":"https://orcid.org/0000-0003-1039-8369"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pin-Yu Chen","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, USA","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016440514","display_name":"Sutanay Choudhury","orcid":"https://orcid.org/0000-0001-7352-2035"},"institutions":[{"id":"https://openalex.org/I142606810","display_name":"Pacific Northwest National Laboratory","ror":"https://ror.org/05h992307","country_code":"US","type":"facility","lineage":["https://openalex.org/I1325736334","https://openalex.org/I1330989302","https://openalex.org/I142606810","https://openalex.org/I39565521"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sutanay Choudhury","raw_affiliation_strings":["Pacific Northwest National Laboratory"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pacific Northwest National Laboratory","institution_ids":["https://openalex.org/I142606810"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077692655","display_name":"Alfred O. Hero","orcid":"https://orcid.org/0000-0002-2531-9670"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alfred O. Hero","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, USA","institution_ids":["https://openalex.org/I27837315"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":36,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4553","last_page":"4557"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9994000196456909,"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"}},"topics":[{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9994000196456909,"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"}},{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9932000041007996,"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/T11476","display_name":"Graph theory and applications","score":0.9793000221252441,"subfield":{"id":"https://openalex.org/subfields/2608","display_name":"Geometry and Topology"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/adjacency-matrix","display_name":"Adjacency matrix","score":0.7558753490447998},{"id":"https://openalex.org/keywords/centrality","display_name":"Centrality","score":0.7468066215515137},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5896019339561462},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5674917101860046},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5327850580215454},{"id":"https://openalex.org/keywords/laplacian-matrix","display_name":"Laplacian matrix","score":0.5204663276672363},{"id":"https://openalex.org/keywords/spectral-graph-theory","display_name":"Spectral graph theory","score":0.5045052766799927},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.4994058609008789},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.49069344997406006},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.47513464093208313},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.4394952654838562},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41551804542541504},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.31407439708709717},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3001699447631836},{"id":"https://openalex.org/keywords/voltage-graph","display_name":"Voltage graph","score":0.22338071465492249},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.2127959132194519},{"id":"https://openalex.org/keywords/line-graph","display_name":"Line graph","score":0.1985592246055603},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.12012606859207153}],"concepts":[{"id":"https://openalex.org/C180356752","wikidata":"https://www.wikidata.org/wiki/Q727035","display_name":"Adjacency matrix","level":3,"score":0.7558753490447998},{"id":"https://openalex.org/C53811970","wikidata":"https://www.wikidata.org/wiki/Q5062194","display_name":"Centrality","level":2,"score":0.7468066215515137},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5896019339561462},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5674917101860046},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5327850580215454},{"id":"https://openalex.org/C115178988","wikidata":"https://www.wikidata.org/wiki/Q772067","display_name":"Laplacian matrix","level":3,"score":0.5204663276672363},{"id":"https://openalex.org/C74003402","wikidata":"https://www.wikidata.org/wiki/Q3180727","display_name":"Spectral graph theory","level":5,"score":0.5045052766799927},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.4994058609008789},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.49069344997406006},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.47513464093208313},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.4394952654838562},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41551804542541504},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.31407439708709717},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3001699447631836},{"id":"https://openalex.org/C22149727","wikidata":"https://www.wikidata.org/wiki/Q7940747","display_name":"Voltage graph","level":4,"score":0.22338071465492249},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.2127959132194519},{"id":"https://openalex.org/C203776342","wikidata":"https://www.wikidata.org/wiki/Q1378376","display_name":"Line graph","level":3,"score":0.1985592246055603},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.12012606859207153},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2016.7472539","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2016.7472539","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.75}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W348531675","https://openalex.org/W1514107797","https://openalex.org/W1540550726","https://openalex.org/W1561952489","https://openalex.org/W1781665229","https://openalex.org/W1875112053","https://openalex.org/W1967570846","https://openalex.org/W1971937094","https://openalex.org/W1981260883","https://openalex.org/W1985336413","https://openalex.org/W1996816151","https://openalex.org/W2012909434","https://openalex.org/W2030319053","https://openalex.org/W2030643321","https://openalex.org/W2031163547","https://openalex.org/W2031842342","https://openalex.org/W2032280284","https://openalex.org/W2049947817","https://openalex.org/W2055828595","https://openalex.org/W2070255353","https://openalex.org/W2089554624","https://openalex.org/W2101491865","https://openalex.org/W2106210113","https://openalex.org/W2113606819","https://openalex.org/W2124543570","https://openalex.org/W2149532724","https://openalex.org/W2160547390","https://openalex.org/W2160660350","https://openalex.org/W2963382956","https://openalex.org/W3161677312","https://openalex.org/W4238452917","https://openalex.org/W6638222449","https://openalex.org/W6676903177"],"related_works":["https://openalex.org/W2557541666","https://openalex.org/W4386468270","https://openalex.org/W4386468337","https://openalex.org/W4254484011","https://openalex.org/W2614668157","https://openalex.org/W2346372059","https://openalex.org/W2030274157","https://openalex.org/W2087450608","https://openalex.org/W1533309322","https://openalex.org/W2549624392"],"abstract_inverted_index":{"Many":[0],"modern":[1],"datasets":[2],"can":[3,19,126,137],"be":[4,20,127],"represented":[5],"as":[6,13],"graphs":[7],"and":[8,56,70,94,135],"hence":[9],"spectral":[10,50,113],"decompositions":[11],"such":[12],"graph":[14,25,43,54,57,65,71,87,91,106],"principal":[15],"component":[16],"analysis":[17],"(PCA)":[18],"useful.":[21],"Distinct":[22],"from":[23],"previous":[24],"decomposition":[26,51,114],"approaches":[27,52],"based":[28,111],"on":[29,112],"subspace":[30],"projection":[31],"of":[32,41,102,115,131],"a":[33,81,95],"single":[34,86],"topological":[35],"feature,":[36],"e.g.,":[37],"the":[38],"Fiedler":[39],"vector":[40],"centered":[42],"adjacency":[44],"matrix":[45],"(graph":[46],"Laplacian),":[47],"we":[48,79],"propose":[49,80],"to":[53,73,121],"PCA":[55,83,92],"dictionary":[58,97,107],"learning":[59,98,108],"that":[60],"integrate":[61],"multiple":[62],"features,":[63],"including":[64],"walk":[66],"statistics,":[67],"centrality":[68],"measures":[69],"distances":[72],"reference":[74],"nodes.":[75],"In":[76],"this":[77],"paper":[78],"new":[82,96],"method":[84,99],"for":[85,100,141],"analysis,":[88],"called":[89,104],"multi-centrality":[90,105,116],"(MC-GPCA),":[93],"ensembles":[101],"graphs,":[103],"(MC-GDL),":[109],"both":[110],"matrices.":[117],"As":[118],"an":[119,128],"application":[120],"cyber":[122],"intrusion":[123],"detection,":[124],"MC-GPCA":[125],"effective":[129],"indicator":[130],"anomalous":[132],"connectivity":[133],"pattern":[134],"MC-GDL":[136],"provide":[138],"discriminative":[139],"basis":[140],"attack":[142],"classification.":[143]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":9},{"year":2016,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}