{"id":"https://openalex.org/W1978907961","doi":"https://doi.org/10.1109/mlsp.2012.6349793","title":"Sequential anomaly detection in a batch with growing number of tests: Application to network intrusion detection","display_name":"Sequential anomaly detection in a batch with growing number of tests: Application to network intrusion detection","publication_year":2012,"publication_date":"2012-09-01","ids":{"openalex":"https://openalex.org/W1978907961","doi":"https://doi.org/10.1109/mlsp.2012.6349793","mag":"1978907961"},"language":"en","primary_location":{"id":"doi:10.1109/mlsp.2012.6349793","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp.2012.6349793","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE International Workshop on Machine Learning for Signal Processing","raw_type":"proceedings-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/A5101739086","display_name":"David J. Miller","orcid":"https://orcid.org/0000-0001-8848-1643"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"David J. Miller","raw_affiliation_strings":["Department of Electrical Engineering, Pennsylvania State University, University Park, PA, USA","Department of Electrical Engineering The Pennsylvania State University, University Park, 16802, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Pennsylvania State University, University Park, PA, USA","institution_ids":["https://openalex.org/I130769515"]},{"raw_affiliation_string":"Department of Electrical Engineering The Pennsylvania State University, University Park, 16802, USA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102096232","display_name":"Fatih Ko\u00e7ak","orcid":null},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fatih Kocak","raw_affiliation_strings":["Department of Electrical Engineering, Pennsylvania State University, University Park, PA, USA","Department of Electrical Engineering The Pennsylvania State University, University Park, 16802, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Pennsylvania State University, University Park, PA, USA","institution_ids":["https://openalex.org/I130769515"]},{"raw_affiliation_string":"Department of Electrical Engineering The Pennsylvania State University, University Park, 16802, USA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063903486","display_name":"George Kesidis","orcid":"https://orcid.org/0000-0001-7947-8127"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"George Kesidis","raw_affiliation_strings":["Department of Electrical Engineering, Department of Computer Science and Engineering, Pennsylvania State University, University Park, PA, USA","Department of Electrical Engineering The Pennsylvania State University, University Park, 16802, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Department of Computer Science and Engineering, Pennsylvania State University, University Park, PA, USA","institution_ids":["https://openalex.org/I130769515"]},{"raw_affiliation_string":"Department of Electrical Engineering The Pennsylvania State University, University Park, 16802, USA","institution_ids":["https://openalex.org/I130769515"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101739086"],"corresponding_institution_ids":["https://openalex.org/I130769515"],"apc_list":null,"apc_paid":null,"fwci":2.1407,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.87887369,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"6","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","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/T11512","display_name":"Anomaly Detection Techniques and Applications","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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9998000264167786,"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/T12391","display_name":"Artificial Immune Systems Applications","score":0.9937999844551086,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6170016527175903},{"id":"https://openalex.org/keywords/intrusion-detection-system","display_name":"Intrusion detection system","score":0.5940849184989929},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5469293594360352},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5278784036636353},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.525638222694397},{"id":"https://openalex.org/keywords/statistical-hypothesis-testing","display_name":"Statistical hypothesis testing","score":0.5216996073722839},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4931904673576355},{"id":"https://openalex.org/keywords/false-alarm","display_name":"False alarm","score":0.4560035467147827},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.42213401198387146},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35476046800613403},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3083230257034302},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.19078361988067627}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6170016527175903},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.5940849184989929},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5469293594360352},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5278784036636353},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.525638222694397},{"id":"https://openalex.org/C87007009","wikidata":"https://www.wikidata.org/wiki/Q210832","display_name":"Statistical hypothesis testing","level":2,"score":0.5216996073722839},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4931904673576355},{"id":"https://openalex.org/C2776836416","wikidata":"https://www.wikidata.org/wiki/Q1364844","display_name":"False alarm","level":2,"score":0.4560035467147827},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.42213401198387146},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35476046800613403},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3083230257034302},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.19078361988067627},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mlsp.2012.6349793","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp.2012.6349793","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE International Workshop on Machine Learning for Signal Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.6200000047683716}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W396053900","https://openalex.org/W2038819732","https://openalex.org/W2064039105","https://openalex.org/W2107551505","https://openalex.org/W2121044470","https://openalex.org/W2122192957","https://openalex.org/W2133990480","https://openalex.org/W2138153039","https://openalex.org/W2168175751","https://openalex.org/W2406037958","https://openalex.org/W6713761039"],"related_works":["https://openalex.org/W2357468538","https://openalex.org/W1577110157","https://openalex.org/W2355007334","https://openalex.org/W2390009783","https://openalex.org/W4254602698","https://openalex.org/W2394461323","https://openalex.org/W2349441905","https://openalex.org/W2361044160","https://openalex.org/W3120792425","https://openalex.org/W1483130311"],"abstract_inverted_index":{"For":[0],"high":[1],"(N)-dimensional":[2],"feature":[3,72,88,135,239],"spaces,":[4],"we":[5,142],"consider":[6],"detection":[7,51,148],"of":[8,13,18,57,79,112,154,181,202],"an":[9],"unknown,":[10,48],"anomalous":[11],"class":[12],"samples":[14,20,30],"amongst":[15,231],"a":[16,46,58,76,144,151,208,220],"batch":[17],"collected":[19],"(of":[21],"size":[22],"T),":[23],"under":[24],"the":[25,32,37,43,64,69,95,113,117,189],"null":[26,65],"hypothesis":[27],"that":[28,237],"all":[29,84,87,100,203],"follow":[31],"same":[33],"probability":[34],"law.":[35],"Since":[36],"features":[38],"which":[39],"will":[40,175],"best":[41],"identify":[42],"anomalies":[44],"are":[45,159,165],"priori":[47],"several":[49],"common":[50],"strategies":[52],"are:":[53],"1)":[54],"evaluating":[55],"atypicality":[56],"sample":[59],"(its":[60],"p-value)":[61],"based":[62,93],"on":[63,68,94,109],"distribution":[66],"defined":[67],"full":[70],"N-dimensional":[71],"space;":[73],"2)":[74],"considering":[75],"(combinatoric)":[77],"set":[78],"low":[80,102],"order":[81,103],"distributions,":[82],"e.g.":[83],"singletons":[85],"and":[86,128],"pairs,":[89],"with":[90,150,216],"detections":[91,185,204],"made":[92,205],"smallest":[96],"p-value":[97],"yielded":[98],"over":[99],"such":[101],"tests.":[104,155],"The":[105],"first":[106],"approach":[107,194],"relies":[108],"accurate":[110],"estimation":[111],"joint":[114],"distribution,":[115],"while":[116],"second":[118],"may":[119],"suffer":[120],"from":[121,246],"increased":[122],"false":[123],"alarm":[124],"rates":[125],"as":[126],"N":[127],"T":[129],"grow.":[130],"Alternatively,":[131],"inspired":[132],"by":[133],"greedy":[134],"selection":[136],"commonly":[137],"used":[138],"in":[139],"supervised":[140,217],"learning,":[141],"propose":[143],"novel":[145],"sequential":[146],"anomaly":[147],"procedure":[149],"growing":[152],"number":[153],"Here,":[156],"new":[157],"tests":[158],"(greedily)":[160],"included":[161],"only":[162],"when":[163,168],"they":[164],"needed,":[166],"i.e.,":[167],"their":[169],"use":[170],"(on":[171],"currently":[172],"undetected":[173],"samples)":[174],"yield":[176],"greater":[177],"aggregate":[178,199],"statistical":[179,200],"significance":[180,201],"(multiple":[182],"testing":[183],"corrected)":[184],"than":[186],"obtainable":[187],"using":[188],"existing":[190],"test":[191],"cadre.":[192],"Our":[193,211],"thus":[195],"aims":[196],"to":[197],"maximize":[198],"up":[206],"until":[207],"finite":[209],"horizon.":[210],"method":[212],"is":[213,235,241],"evaluated,":[214],"along":[215],"methods,":[218],"for":[219,243],"network":[221],"intrusion":[222],"domain,":[223],"detecting":[224],"Zeus":[225,245],"bot":[226],"(intrusion)":[227],"packet":[228],"flows":[229],"embedded":[230],"(normal)Web":[232],"flows.":[233],"It":[234],"shown":[236],"judicious":[238],"representation":[240],"essential":[242],"discriminating":[244],"Web.":[247]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}