{"id":"https://openalex.org/W2495570269","doi":"https://doi.org/10.1147/jrd.2016.2558018","title":"Firstfilter: A cost-sensitive approach to malicious URL detection in large-scale enterprise networks","display_name":"Firstfilter: A cost-sensitive approach to malicious URL detection in large-scale enterprise networks","publication_year":2016,"publication_date":"2016-07-01","ids":{"openalex":"https://openalex.org/W2495570269","doi":"https://doi.org/10.1147/jrd.2016.2558018","mag":"2495570269"},"language":"en","primary_location":{"id":"doi:10.1147/jrd.2016.2558018","is_oa":false,"landing_page_url":"https://doi.org/10.1147/jrd.2016.2558018","pdf_url":null,"source":{"id":"https://openalex.org/S4210219925","display_name":"IBM Journal of Research and Development","issn_l":"0018-8646","issn":["0018-8646","2151-8556"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320652","host_organization_name":"IBM","host_organization_lineage":["https://openalex.org/P4310320652"],"host_organization_lineage_names":["IBM"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IBM Journal of Research and Development","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/A5038966811","display_name":"Long Vu","orcid":"https://orcid.org/0000-0002-3586-8630"},"institutions":[{"id":"https://openalex.org/I4210114115","display_name":"IBM Research - Thomas J. Watson Research Center","ror":"https://ror.org/0265w5591","country_code":"US","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"L. Vu","raw_affiliation_strings":["IBM Research Division, Thomas J. Watson Research Center, Yorktown Heights, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research Division, Thomas J. Watson Research Center, Yorktown Heights, NY, USA","institution_ids":["https://openalex.org/I4210114115"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023235306","display_name":"Phuong T. Nguyen","orcid":"https://orcid.org/0000-0002-3666-4162"},"institutions":[{"id":"https://openalex.org/I4210114115","display_name":"IBM Research - Thomas J. Watson Research Center","ror":"https://ror.org/0265w5591","country_code":"US","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"P. Nguyen","raw_affiliation_strings":["IBM Research Division, Thomas J. Watson Research Center, Yorktown Heights, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research Division, Thomas J. Watson Research Center, Yorktown Heights, NY, USA","institution_ids":["https://openalex.org/I4210114115"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056925015","display_name":"Deepak S. Turaga","orcid":null},"institutions":[{"id":"https://openalex.org/I4210114115","display_name":"IBM Research - Thomas J. Watson Research Center","ror":"https://ror.org/0265w5591","country_code":"US","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"D. Turaga","raw_affiliation_strings":["IBM Research Division, Thomas J. Watson Research Center, Yorktown Heights, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research Division, Thomas J. Watson Research Center, Yorktown Heights, NY, USA","institution_ids":["https://openalex.org/I4210114115"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.0711,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.90037043,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"60","issue":"4","first_page":"4:1","last_page":"4:10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11644","display_name":"Spam and Phishing Detection","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T11644","display_name":"Spam and Phishing Detection","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.9994999766349792,"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/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.9990000128746033,"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":0.7865381240844727},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6795158386230469},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5347750186920166},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5282869935035706},{"id":"https://openalex.org/keywords/binary-classification","display_name":"Binary classification","score":0.5169024467468262},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.466886430978775},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44543343782424927},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43483179807662964},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.42837560176849365},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.14372849464416504},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.12620508670806885}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7865381240844727},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6795158386230469},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5347750186920166},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5282869935035706},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.5169024467468262},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.466886430978775},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44543343782424927},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43483179807662964},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.42837560176849365},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.14372849464416504},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.12620508670806885},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"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},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1147/jrd.2016.2558018","is_oa":false,"landing_page_url":"https://doi.org/10.1147/jrd.2016.2558018","pdf_url":null,"source":{"id":"https://openalex.org/S4210219925","display_name":"IBM Journal of Research and Development","issn_l":"0018-8646","issn":["0018-8646","2151-8556"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320652","host_organization_name":"IBM","host_organization_lineage":["https://openalex.org/P4310320652"],"host_organization_lineage_names":["IBM"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IBM Journal of Research and Development","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W24863754","https://openalex.org/W113692204","https://openalex.org/W1584308190","https://openalex.org/W1954903228","https://openalex.org/W1975909792","https://openalex.org/W1990089904","https://openalex.org/W1990497396","https://openalex.org/W2040564948","https://openalex.org/W2058732827","https://openalex.org/W2082550445","https://openalex.org/W2100390153","https://openalex.org/W2111165162","https://openalex.org/W2152929147","https://openalex.org/W2158568356","https://openalex.org/W2160289821","https://openalex.org/W2163764145","https://openalex.org/W2295731716","https://openalex.org/W2401054255","https://openalex.org/W2460383888","https://openalex.org/W2974760584","https://openalex.org/W6601016221","https://openalex.org/W6604639599","https://openalex.org/W6635269506","https://openalex.org/W6676847925","https://openalex.org/W6696870837","https://openalex.org/W6713023146","https://openalex.org/W6719031813"],"related_works":["https://openalex.org/W2140798747","https://openalex.org/W2948169060","https://openalex.org/W2730112582","https://openalex.org/W2110696645","https://openalex.org/W2358580169","https://openalex.org/W2046798493","https://openalex.org/W4382934300","https://openalex.org/W2121061354","https://openalex.org/W4285388059","https://openalex.org/W1997162386"],"abstract_inverted_index":{"We":[0,61],"present":[1],"Firstfilter,":[2],"a":[3,30],"new":[4],"cost-sensitive":[5,59],"classifier":[6],"that":[7,88],"detects":[8],"malicious":[9],"Uniform":[10],"Resource":[11],"Locations":[12],"(URLs)":[13],"in":[14],"large-scale":[15,66],"enterprise":[16,72],"networks.":[17],"Firstfilter":[18,63,89],"classifies":[19],"an":[20,48,71],"input":[21],"URL":[22],"as":[23],"benign,":[24],"unknown,":[25],"or":[26],"malicious,":[27],"and":[28,39,94],"utilizes":[29],"cost":[31,45],"matrix":[32,46],"to":[33,40,51,81],"select":[34],"the":[35,58],"most":[36],"relevant":[37],"features":[38],"control":[41],"model":[42],"misclassifications.":[43],"The":[44],"provides":[47],"effective":[49],"tool":[50],"fine":[52],"tune":[53],"key":[54],"performance":[55],"metrics":[56],"of":[57],"classifier.":[60],"evaluate":[62],"extensively":[64],"with":[65],"network":[67,73],"datasets":[68],"collected":[69],"from":[70,78],"for":[74],"three":[75],"months,":[76],"spanning":[77],"June":[79],"2015":[80],"August":[82],"2015.":[83],"Our":[84],"evaluation":[85],"results":[86],"show":[87],"consistently":[90],"outperforms":[91],"cost-insensitive":[92],"classifiers":[93],"other":[95],"binary":[96],"classifiers.":[97]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
