{"id":"https://openalex.org/W2916401208","doi":"https://doi.org/10.1109/glocom.2018.8647679","title":"DNS Typo-Squatting Domain Detection: A Data Analytics & Machine Learning Based Approach","display_name":"DNS Typo-Squatting Domain Detection: A Data Analytics & Machine Learning Based Approach","publication_year":2018,"publication_date":"2018-12-01","ids":{"openalex":"https://openalex.org/W2916401208","doi":"https://doi.org/10.1109/glocom.2018.8647679","mag":"2916401208"},"language":"en","primary_location":{"id":"doi:10.1109/glocom.2018.8647679","is_oa":false,"landing_page_url":"https://doi.org/10.1109/glocom.2018.8647679","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE Global Communications Conference (GLOBECOM)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2012.13604","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Abdallah Moubayed","orcid":null},"institutions":[{"id":"https://openalex.org/I125749732","display_name":"Western University","ror":"https://ror.org/02grkyz14","country_code":"CA","type":"education","lineage":["https://openalex.org/I125749732"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Abdallah Moubayed","raw_affiliation_strings":["Western University, London, Ontario, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Western University, London, Ontario, Canada","institution_ids":["https://openalex.org/I125749732"]}]},{"author_position":"middle","author":{"id":null,"display_name":"MohammadNoor Injadat","orcid":null},"institutions":[{"id":"https://openalex.org/I125749732","display_name":"Western University","ror":"https://ror.org/02grkyz14","country_code":"CA","type":"education","lineage":["https://openalex.org/I125749732"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"MohammadNoor Injadat","raw_affiliation_strings":["Western University, London, Ontario, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Western University, London, Ontario, Canada","institution_ids":["https://openalex.org/I125749732"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Abdallah Shami","orcid":null},"institutions":[{"id":"https://openalex.org/I125749732","display_name":"Western University","ror":"https://ror.org/02grkyz14","country_code":"CA","type":"education","lineage":["https://openalex.org/I125749732"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Abdallah Shami","raw_affiliation_strings":["Western University, London, Ontario, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Western University, London, Ontario, Canada","institution_ids":["https://openalex.org/I125749732"]}]},{"author_position":"last","author":{"id":null,"display_name":"Hanan Lutfiyya","orcid":null},"institutions":[{"id":"https://openalex.org/I125749732","display_name":"Western University","ror":"https://ror.org/02grkyz14","country_code":"CA","type":"education","lineage":["https://openalex.org/I125749732"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Hanan Lutfiyya","raw_affiliation_strings":["Western University, London, Ontario, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Western University, London, Ontario, Canada","institution_ids":["https://openalex.org/I125749732"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I125749732"],"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":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9993000030517578,"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/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/classifier","display_name":"Classifier (UML)","score":0.7105000019073486},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6988000273704529},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.5752999782562256},{"id":"https://openalex.org/keywords/commit","display_name":"Commit","score":0.4918000102043152},{"id":"https://openalex.org/keywords/domain-name-system","display_name":"Domain Name System","score":0.44449999928474426},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.44029998779296875},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.4101000130176544},{"id":"https://openalex.org/keywords/statistical-classification","display_name":"Statistical classification","score":0.4065000116825104}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7904000282287598},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.7105000019073486},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6988000273704529},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6588000059127808},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6419000029563904},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.5752999782562256},{"id":"https://openalex.org/C153180980","wikidata":"https://www.wikidata.org/wiki/Q19776675","display_name":"Commit","level":2,"score":0.4918000102043152},{"id":"https://openalex.org/C35026560","wikidata":"https://www.wikidata.org/wiki/Q8767","display_name":"Domain Name System","level":3,"score":0.44449999928474426},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.44029998779296875},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.42800000309944153},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.4101000130176544},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.4065000116825104},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.32659998536109924},{"id":"https://openalex.org/C199190896","wikidata":"https://www.wikidata.org/wiki/Q3509276","display_name":"Learning classifier system","level":3,"score":0.30149999260902405},{"id":"https://openalex.org/C207968372","wikidata":"https://www.wikidata.org/wiki/Q310401","display_name":"k-means clustering","level":3,"score":0.29980000853538513},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.28529998660087585},{"id":"https://openalex.org/C2780264999","wikidata":"https://www.wikidata.org/wiki/Q7445032","display_name":"Security domain","level":2,"score":0.2842999994754791},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.27950000762939453},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2721000015735626},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.2639000117778778},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.2502000033855438}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/glocom.2018.8647679","is_oa":false,"landing_page_url":"https://doi.org/10.1109/glocom.2018.8647679","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE Global Communications Conference (GLOBECOM)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2012.13604","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2012.13604","pdf_url":"https://arxiv.org/pdf/2012.13604","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2012.13604","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2012.13604","pdf_url":"https://arxiv.org/pdf/2012.13604","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W2037998200","https://openalex.org/W2053598121","https://openalex.org/W2096904130","https://openalex.org/W2104197273","https://openalex.org/W2785495041","https://openalex.org/W2793666160","https://openalex.org/W6606832826","https://openalex.org/W6640663528","https://openalex.org/W6676367512"],"related_works":[],"abstract_inverted_index":{"Domain":[0],"Name":[1],"System":[2],"(DNS)":[3],"is":[4,14,36,46,51,80,93,120,189,198,209,216,230],"a":[5,39,58,76,109,163,234],"crucial":[6],"component":[7],"of":[8,28,41,182,203,224,236,246],"current":[9],"IP-based":[10],"networks":[11],"as":[12,54,206,227],"it":[13,35,55,188],"the":[15,84,99,131,138,152,173,201,212,222,241],"standard":[16],"mechanism":[17],"for":[18],"name":[19,166],"to":[20,25,38,60,67,82,96],"IP":[21],"resolution.":[22],"However,":[23,200],"due":[24],"its":[26],"lack":[27],"data":[29,91],"integrity":[30],"and":[31,63,149,168,185],"origin":[32],"authentication":[33],"processes,":[34],"vulnerable":[37],"variety":[40],"attacks.":[42],"One":[43],"such":[44],"attack":[45,50],"Typosquatting.":[47],"Detecting":[48],"this":[49,74],"particularly":[52],"important":[53],"can":[56,64,123],"be":[57,65],"threat":[59],"corporate":[61],"secrets":[62],"used":[66,95],"steal":[68],"information":[69],"or":[70],"commit":[71],"fraud.":[72],"In":[73],"paper,":[75],"machine":[77],"learning-based":[78],"approach":[79],"proposed":[81,121],"tackle":[83],"typosquatting":[85],"vulnerability.":[86],"To":[87],"that":[88,122,159,191,221],"end,":[89],"exploratory":[90],"analytics":[92],"first":[94],"better":[97,179],"understand":[98],"trends":[100,133,193,243],"observed":[101,132,195],"in":[102,141,180,244],"eight":[103],"domain":[104,165],"name-based":[105],"extracted":[106],"features.":[107],"Furthermore,":[108,187],"majority":[110],"voting-based":[111],"ensemble":[112,154,175,213],"learning":[113,155,176,214],"classifier":[114,177,215],"built":[115],"using":[116,145],"five":[117,237],"classification":[118],"algorithms":[119],"detect":[124],"suspicious":[125,208,229],"domains":[126,161,204,225],"with":[127,218],"high":[128],"accuracy.":[129],"Moreover,":[130,172],"are":[134,194],"validated":[135],"by":[136,232],"studying":[137],"same":[139,242],"features":[140],"an":[142],"unlabeled":[143],"dataset":[144],"K-means":[146],"clustering":[147,197],"algorithm":[148],"through":[150],"applying":[151],"developed":[153,174],"classifier.":[156],"Results":[157],"show":[158],"legitimate":[160],"have":[162],"smaller":[164],"length":[167],"fewer":[169],"unique":[170],"characters.":[171],"performs":[178],"terms":[181,245],"accuracy,":[183],"precision,":[184],"F-score.":[186],"shown":[190],"similar":[192],"when":[196],"used.":[199],"number":[202,223],"identified":[205,226],"potentially":[207,228],"high.":[210],"Hence,":[211],"applied":[217],"results":[219],"showing":[220],"reduced":[231],"almost":[233],"factor":[235],"while":[238],"still":[239],"maintaining":[240],"features'":[247],"statistics.":[248]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":12},{"year":2019,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2019-03-02T00:00:00"}