{"id":"https://openalex.org/W2081556513","doi":"https://doi.org/10.4018/jisp.2007100103","title":"E-Mail Worm Detection Using Data Mining","display_name":"E-Mail Worm Detection Using Data Mining","publication_year":2007,"publication_date":"2007-10-01","ids":{"openalex":"https://openalex.org/W2081556513","doi":"https://doi.org/10.4018/jisp.2007100103","mag":"2081556513"},"language":"en","primary_location":{"id":"doi:10.4018/jisp.2007100103","is_oa":false,"landing_page_url":"https://doi.org/10.4018/jisp.2007100103","pdf_url":null,"source":{"id":"https://openalex.org/S191782446","display_name":"International Journal of Information Security and Privacy","issn_l":"1930-1650","issn":["1930-1650","1930-1669"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Information Security and Privacy","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/A5029798067","display_name":"Mohammad Mehedy Masud","orcid":"https://orcid.org/0000-0002-5274-5982"},"institutions":[{"id":"https://openalex.org/I162577319","display_name":"The University of Texas at Dallas","ror":"https://ror.org/049emcs32","country_code":"US","type":"education","lineage":["https://openalex.org/I162577319"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Mohammad M. Masud","raw_affiliation_strings":["The University of Texas at Dallas, USA"],"affiliations":[{"raw_affiliation_string":"The University of Texas at Dallas, USA","institution_ids":["https://openalex.org/I162577319"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005002693","display_name":"Latifur Khan","orcid":"https://orcid.org/0000-0002-9300-1576"},"institutions":[{"id":"https://openalex.org/I162577319","display_name":"The University of Texas at Dallas","ror":"https://ror.org/049emcs32","country_code":"US","type":"education","lineage":["https://openalex.org/I162577319"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Latifur Khan","raw_affiliation_strings":["The University of Texas at Dallas, USA"],"affiliations":[{"raw_affiliation_string":"The University of Texas at Dallas, USA","institution_ids":["https://openalex.org/I162577319"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072193842","display_name":"Bhavani Thuraisingham","orcid":"https://orcid.org/0000-0003-4653-2080"},"institutions":[{"id":"https://openalex.org/I162577319","display_name":"The University of Texas at Dallas","ror":"https://ror.org/049emcs32","country_code":"US","type":"education","lineage":["https://openalex.org/I162577319"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bhavani Thuraisingham","raw_affiliation_strings":["The University of Texas at Dallas, USA"],"affiliations":[{"raw_affiliation_string":"The University of Texas at Dallas, USA","institution_ids":["https://openalex.org/I162577319"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5029798067"],"corresponding_institution_ids":["https://openalex.org/I162577319"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.11800235,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"1","issue":"4","first_page":"47","last_page":"61"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11644","display_name":"Spam and Phishing Detection","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9993000030517578,"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":0.9988999962806702,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8187692165374756},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.6871793270111084},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6846679449081421},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6400887370109558},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.6206498742103577},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5923746228218079},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.5820586681365967},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.5095265507698059},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.5072514414787292},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.4850420355796814},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.473409503698349},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4623625874519348},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34408414363861084}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8187692165374756},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6871793270111084},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6846679449081421},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6400887370109558},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.6206498742103577},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5923746228218079},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.5820586681365967},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.5095265507698059},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.5072514414787292},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.4850420355796814},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.473409503698349},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4623625874519348},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34408414363861084},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.4018/jisp.2007100103","is_oa":false,"landing_page_url":"https://doi.org/10.4018/jisp.2007100103","pdf_url":null,"source":{"id":"https://openalex.org/S191782446","display_name":"International Journal of Information Security and Privacy","issn_l":"1930-1650","issn":["1930-1650","1930-1669"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Information Security and Privacy","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:igg:jisp00:v:1:y:2007:i:4:p:47-61","is_oa":false,"landing_page_url":"https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/jisp.2007100103","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":2,"referenced_works":["https://openalex.org/W1981589225","https://openalex.org/W2169300738"],"related_works":["https://openalex.org/W2156571267","https://openalex.org/W4389954502","https://openalex.org/W2771255398","https://openalex.org/W20047544","https://openalex.org/W2747166117","https://openalex.org/W2930428186","https://openalex.org/W3200027047","https://openalex.org/W3125536479","https://openalex.org/W4378417285","https://openalex.org/W4214820172"],"abstract_inverted_index":{"This":[0,71],"work":[1],"applies":[2],"data":[3,114],"mining":[4],"techniques":[5,123],"to":[6,41,75,117],"detect":[7],"e-mail":[8],"worms.":[9,154,187],"E-mail":[10],"messages":[11],"contain":[12],"a":[13,93,119,145],"number":[14,22,59],"of":[15,23,29,33,54,60,96,153,186],"different":[16,66],"features":[17,61],"such":[18,127],"as":[19,128],"the":[20,58,81,112,139,167,176],"total":[21],"words":[24],"in":[25,179],"message":[26],"body/subject,":[27],"presence/absence":[28],"binary":[30],"attachments,":[31,34],"type":[32],"and":[35,69,78,99,135,150,183],"so":[36],"on.":[37],"The":[38,51,83,103],"goal":[39],"is":[40,62,73,86,92,105,115,164],"obtain":[42],"an":[43],"efficient":[44],"classification":[45,122,174],"model":[46],"based":[47],"on":[48,144],"these":[49],"features.":[50],"solution":[52],"consists":[53],"several":[55],"steps.":[56],"First,":[57],"reduced":[63,113],"using":[64],"two":[65],"approaches:":[67],"feature-selection":[68,84],"dimension-reduction.":[70],"step":[72],"necessary":[74],"reduce":[76],"noise":[77],"redundancy":[79],"from":[80],"data.":[82],"technique":[85],"called":[87],"Two-phase":[88],"Selection":[89],"(TPS),":[90],"which":[91],"novel":[94],"combination":[95],"decision":[97],"tree":[98],"greedy":[100],"selection":[101,170],"algorithm.":[102],"dimension-reduction":[104],"performed":[106],"by":[107],"Principal":[108],"Component":[109],"Analysis.":[110],"Second,":[111],"used":[116],"train":[118],"classifier.":[120],"Different":[121],"have":[124,157],"been":[125,158],"used,":[126],"Support":[129],"Vector":[130],"Machine":[131],"(SVM),":[132],"Na\u00efve":[133],"Bayes,":[134],"their":[136],"combination.":[137],"Finally,":[138],"trained":[140],"classifiers":[141],"are":[142],"tested":[143],"dataset":[146],"containing":[147],"both":[148,181],"known":[149,182],"unknown":[151,184],"types":[152,185],"These":[155],"results":[156],"compared":[159],"with":[160,172],"published":[161],"results.":[162],"It":[163],"found":[165],"that":[166],"proposed":[168],"TPS":[169],"along":[171],"SVM":[173],"achieves":[175],"best":[177],"accuracy":[178],"detecting":[180]},"counts_by_year":[{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
