{"id":"https://openalex.org/W2792910062","doi":"https://doi.org/10.1109/tsipn.2018.2818950","title":"Sparse Laplacian Component Analysis for Internet Traffic Anomalies Detection","display_name":"Sparse Laplacian Component Analysis for Internet Traffic Anomalies Detection","publication_year":2018,"publication_date":"2018-03-23","ids":{"openalex":"https://openalex.org/W2792910062","doi":"https://doi.org/10.1109/tsipn.2018.2818950","mag":"2792910062"},"language":"en","primary_location":{"id":"doi:10.1109/tsipn.2018.2818950","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsipn.2018.2818950","pdf_url":null,"source":{"id":"https://openalex.org/S4306422866","display_name":"IEEE Transactions on Signal and Information Processing over Networks","issn_l":"2373-776X","issn":["2373-776X","2373-7778"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Signal and Information Processing over Networks","raw_type":"journal-article"},"type":"article","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/A5066841329","display_name":"Manas Khatua","orcid":"https://orcid.org/0000-0002-8329-2429"},"institutions":[{"id":"https://openalex.org/I154549908","display_name":"Indian Institute of Technology Jodhpur","ror":"https://ror.org/03yacj906","country_code":"IN","type":"education","lineage":["https://openalex.org/I154549908"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Manas Khatua","raw_affiliation_strings":["Indian Institute of Technology Jodhpur, Jodhpur, India"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology Jodhpur, Jodhpur, India","institution_ids":["https://openalex.org/I154549908"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040076196","display_name":"Seyed Hamid Safavi","orcid":null},"institutions":[{"id":"https://openalex.org/I48379061","display_name":"Shahid Beheshti University","ror":"https://ror.org/0091vmj44","country_code":"IR","type":"education","lineage":["https://openalex.org/I48379061"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Seyed Hamid Safavi","raw_affiliation_strings":["Shahid Beheshti University, Tehran, Iran"],"affiliations":[{"raw_affiliation_string":"Shahid Beheshti University, Tehran, Iran","institution_ids":["https://openalex.org/I48379061"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057453537","display_name":"Ngai\u2010Man Cheung","orcid":"https://orcid.org/0000-0003-0135-3791"},"institutions":[{"id":"https://openalex.org/I152815399","display_name":"Singapore University of Technology and Design","ror":"https://ror.org/05j6fvn87","country_code":"SG","type":"education","lineage":["https://openalex.org/I152815399"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Ngai-Man Cheung","raw_affiliation_strings":["Singapore University of Technology and Design, Singapore"],"affiliations":[{"raw_affiliation_string":"Singapore University of Technology and Design, Singapore","institution_ids":["https://openalex.org/I152815399"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5066841329"],"corresponding_institution_ids":["https://openalex.org/I154549908"],"apc_list":null,"apc_paid":null,"fwci":0.7381,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.7343039,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"4","issue":"4","first_page":"697","last_page":"711"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9997000098228455,"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":0.9997000098228455,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9984999895095825,"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/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.9973999857902527,"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/subspace-topology","display_name":"Subspace topology","score":0.7464997172355652},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6421601176261902},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.6229271292686462},{"id":"https://openalex.org/keywords/linear-subspace","display_name":"Linear subspace","score":0.5955169200897217},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.530360758304596},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5256506204605103},{"id":"https://openalex.org/keywords/laplacian-matrix","display_name":"Laplacian matrix","score":0.49037814140319824},{"id":"https://openalex.org/keywords/laplace-operator","display_name":"Laplace operator","score":0.4847983419895172},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.44105106592178345},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36524486541748047},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.33782514929771423},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.33667218685150146},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.31780537962913513},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.223653644323349}],"concepts":[{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.7464997172355652},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6421601176261902},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6229271292686462},{"id":"https://openalex.org/C12362212","wikidata":"https://www.wikidata.org/wiki/Q728435","display_name":"Linear subspace","level":2,"score":0.5955169200897217},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.530360758304596},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5256506204605103},{"id":"https://openalex.org/C115178988","wikidata":"https://www.wikidata.org/wiki/Q772067","display_name":"Laplacian matrix","level":3,"score":0.49037814140319824},{"id":"https://openalex.org/C165700671","wikidata":"https://www.wikidata.org/wiki/Q203484","display_name":"Laplace operator","level":2,"score":0.4847983419895172},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.44105106592178345},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36524486541748047},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33782514929771423},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.33667218685150146},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31780537962913513},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.223653644323349},{"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsipn.2018.2818950","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsipn.2018.2818950","pdf_url":null,"source":{"id":"https://openalex.org/S4306422866","display_name":"IEEE Transactions on Signal and Information Processing over Networks","issn_l":"2373-776X","issn":["2373-776X","2373-7778"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Signal and Information Processing over Networks","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":89,"referenced_works":["https://openalex.org/W1486189686","https://openalex.org/W1530218127","https://openalex.org/W1604400617","https://openalex.org/W1698699930","https://openalex.org/W1800461055","https://openalex.org/W1966809779","https://openalex.org/W1975900269","https://openalex.org/W1991252559","https://openalex.org/W1991574184","https://openalex.org/W1992222322","https://openalex.org/W1994761691","https://openalex.org/W2028302281","https://openalex.org/W2028479713","https://openalex.org/W2029332168","https://openalex.org/W2038819732","https://openalex.org/W2053186076","https://openalex.org/W2058737544","https://openalex.org/W2063978311","https://openalex.org/W2064788805","https://openalex.org/W2065643612","https://openalex.org/W2089554624","https://openalex.org/W2093168265","https://openalex.org/W2097308346","https://openalex.org/W2100273859","https://openalex.org/W2100556411","https://openalex.org/W2101491865","https://openalex.org/W2105934885","https://openalex.org/W2106210113","https://openalex.org/W2116063398","https://openalex.org/W2122646361","https://openalex.org/W2127084909","https://openalex.org/W2130613448","https://openalex.org/W2135957476","https://openalex.org/W2139054829","https://openalex.org/W2140738143","https://openalex.org/W2145962650","https://openalex.org/W2147331788","https://openalex.org/W2149532724","https://openalex.org/W2154872931","https://openalex.org/W2156718197","https://openalex.org/W2157578436","https://openalex.org/W2158787690","https://openalex.org/W2161041254","https://openalex.org/W2210251978","https://openalex.org/W2259160646","https://openalex.org/W2346382359","https://openalex.org/W2509223312","https://openalex.org/W2512573859","https://openalex.org/W2515730783","https://openalex.org/W2531880140","https://openalex.org/W2572321817","https://openalex.org/W2607169934","https://openalex.org/W2679590114","https://openalex.org/W2740334263","https://openalex.org/W2759196042","https://openalex.org/W2783629814","https://openalex.org/W2794319422","https://openalex.org/W2962685284","https://openalex.org/W2963545270","https://openalex.org/W2963813647","https://openalex.org/W2964160020","https://openalex.org/W3148981562","https://openalex.org/W4205419814","https://openalex.org/W4297817021","https://openalex.org/W6631990664","https://openalex.org/W6638268360","https://openalex.org/W6648539833","https://openalex.org/W6649344144","https://openalex.org/W6657573413","https://openalex.org/W6657901550","https://openalex.org/W6675104541","https://openalex.org/W6675653171","https://openalex.org/W6680292251","https://openalex.org/W6682193561","https://openalex.org/W6682644385","https://openalex.org/W6682755970","https://openalex.org/W6683654968","https://openalex.org/W6686785280","https://openalex.org/W6687809340","https://openalex.org/W6725817426","https://openalex.org/W6727449274","https://openalex.org/W6728487162","https://openalex.org/W6733183060","https://openalex.org/W6737727017","https://openalex.org/W6738395051","https://openalex.org/W6740173858","https://openalex.org/W6742450674","https://openalex.org/W6747507538","https://openalex.org/W7071432053"],"related_works":["https://openalex.org/W2896134808","https://openalex.org/W3172436493","https://openalex.org/W4287164812","https://openalex.org/W2957492749","https://openalex.org/W1887135636","https://openalex.org/W2386063599","https://openalex.org/W1975884855","https://openalex.org/W3213150849","https://openalex.org/W4285605394","https://openalex.org/W2025894073"],"abstract_inverted_index":{"We":[0,234,246],"consider":[1],"the":[2,38,77,83,86,89,130,153,172,205,208,216,222,232,249,255,261],"problem":[3,14],"of":[4,16,21,41,85,91,175,207,224],"anomaly":[5,118,239],"detection":[6,240,268],"in":[7,117,125,140],"network":[8,22,52],"traffic.":[9,23],"It":[10],"is":[11,28,104,147],"a":[12,72,107,148,188,199],"challenging":[13],"because":[15],"high-dimensional":[17,39],"and":[18,50,58,79,164,212,265],"noisy":[19],"nature":[20],"A":[24],"popularly":[25],"used":[26],"technique":[27],"subspace":[29,33,259],"analysis.":[30,66,233],"In":[31,67,142],"particular,":[32],"analysis":[34,56,173],"aims":[35],"to":[36,48,75,81,105,110,151,168,177,191,230],"separate":[37],"space":[40],"traffic":[42,264],"signals":[43],"into":[44,129,171],"disjoint":[45],"subspaces":[46],"corresponding":[47],"normal":[49,262],"anomalous":[51],"conditions.":[53],"Principal":[54],"component":[55],"(PCA)":[57],"its":[59,115],"improvements":[60],"have":[61],"been":[62],"applied":[63],"for":[64],"this":[65,68],"work,":[69],"we":[70,95,138,195],"take":[71],"different":[73,127,179,182],"approach":[74],"determine":[76],"subspaces,":[78],"propose":[80,106],"capture":[82],"essence":[84],"data":[87,211,244],"using":[88,241],"eigenvectors":[90],"graph":[92,154,190,202],"Laplacian,":[93],"which":[94,137],"refer":[96],"as":[97,227],"Laplacian":[98],"components":[99,174],"(LCs).":[100],"Our":[101],"main":[102],"contribution":[103,146],"regression":[108],"framework":[109,121,150,160],"compute":[111,152],"LCs":[112,133],"followed":[113],"by":[114],"application":[116],"detection.":[119],"This":[120],"provides":[122],"much":[123],"flexibility":[124],"incorporating":[126],"properties":[128,167],"LCs,":[131],"notably":[132],"with":[134,198],"sparse":[135,162],"loadings,":[136],"exploit":[139],"detail.":[141],"other":[143,166],"words,":[144],"our":[145],"new":[149],"Fourier":[155],"transform":[156],"(GFT).":[157],"The":[158],"proposed":[159,217,250],"enables":[161],"loadings":[163],"potentially":[165],"be":[169],"incorporated":[170],"GFT":[176],"suit":[178],"tasks.":[180],"Furthermore,":[181],"from":[183],"previous":[184],"work":[185],"that":[186,203,248],"uses":[187],"sample":[189],"preserve":[192],"local":[193],"structure,":[194],"advocate":[196],"modeling":[197],"dual-input":[200],"feature":[201],"encodes":[204],"correlation":[206],"time":[209],"series":[210],"prior":[213,228],"information.":[214],"Therefore,":[215],"model":[218,251],"can":[219,252],"readily":[220],"incorporate":[221],"\u201cphysics\u201d":[223],"some":[225],"applications":[226],"information":[229],"improve":[231],"perform":[235],"experiments":[236],"on":[237],"volume":[238],"three":[242],"real":[243],"sets.":[245],"demonstrate":[247],"correctly":[253],"uncover":[254],"essential":[256],"low-dimensional":[257],"principal":[258],"containing":[260],"Internet":[263],"achieve":[266],"outstanding":[267],"performance.":[269]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
