{"id":"https://openalex.org/W3162435697","doi":"https://doi.org/10.1109/ntms49979.2021.9432673","title":"TypoSwype: An Imaging Approach to Detect Typo-Squatting","display_name":"TypoSwype: An Imaging Approach to Detect Typo-Squatting","publication_year":2021,"publication_date":"2021-04-19","ids":{"openalex":"https://openalex.org/W3162435697","doi":"https://doi.org/10.1109/ntms49979.2021.9432673","mag":"3162435697"},"language":"en","primary_location":{"id":"doi:10.1109/ntms49979.2021.9432673","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ntms49979.2021.9432673","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 11th IFIP International Conference on New Technologies, Mobility and Security (NTMS)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2209.00783","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5059075218","display_name":"Lee Joon Sern","orcid":null},"institutions":[{"id":"https://openalex.org/I4210148559","display_name":"\u00c9cole nationale sup\u00e9rieure de techniques avanc\u00e9es Bretagne","ror":"https://ror.org/059n54003","country_code":"FR","type":"education","lineage":["https://openalex.org/I201181511","https://openalex.org/I4210145102","https://openalex.org/I4210148559"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Lee Joon Sern","raw_affiliation_strings":["Ensign InfoSecurity,Ensign Labs,Singapore","Ensign Labs, Ensign InfoSecurity, Singapore"],"affiliations":[{"raw_affiliation_string":"Ensign InfoSecurity,Ensign Labs,Singapore","institution_ids":["https://openalex.org/I4210148559"]},{"raw_affiliation_string":"Ensign Labs, Ensign InfoSecurity, Singapore","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030517958","display_name":"Yam Gui Peng David","orcid":null},"institutions":[{"id":"https://openalex.org/I4210148559","display_name":"\u00c9cole nationale sup\u00e9rieure de techniques avanc\u00e9es Bretagne","ror":"https://ror.org/059n54003","country_code":"FR","type":"education","lineage":["https://openalex.org/I201181511","https://openalex.org/I4210145102","https://openalex.org/I4210148559"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Yam Gui Peng David","raw_affiliation_strings":["Ensign InfoSecurity,Ensign Labs,Singapore","Ensign Labs, Ensign InfoSecurity, Singapore"],"affiliations":[{"raw_affiliation_string":"Ensign InfoSecurity,Ensign Labs,Singapore","institution_ids":["https://openalex.org/I4210148559"]},{"raw_affiliation_string":"Ensign Labs, Ensign InfoSecurity, Singapore","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5059075218"],"corresponding_institution_ids":["https://openalex.org/I4210148559"],"apc_list":null,"apc_paid":null,"fwci":0.4616,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.60089957,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9998000264167786,"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"}},{"id":"https://openalex.org/T12034","display_name":"Digital and Cyber Forensics","score":0.9975000023841858,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9937000274658203,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.7170126438140869},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.64570152759552},{"id":"https://openalex.org/keywords/squatting-position","display_name":"Squatting position","score":0.6174236536026001},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.6027988791465759},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.6002020835876465},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5597558617591858},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5593182444572449},{"id":"https://openalex.org/keywords/malware","display_name":"Malware","score":0.5400062799453735},{"id":"https://openalex.org/keywords/string","display_name":"String (physics)","score":0.46447765827178955},{"id":"https://openalex.org/keywords/edit-distance","display_name":"Edit distance","score":0.43247509002685547},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4128343462944031},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3944114148616791},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3446786403656006},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15095776319503784},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.08640500903129578}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7170126438140869},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.64570152759552},{"id":"https://openalex.org/C119971845","wikidata":"https://www.wikidata.org/wiki/Q2540134","display_name":"Squatting position","level":2,"score":0.6174236536026001},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.6027988791465759},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6002020835876465},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5597558617591858},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5593182444572449},{"id":"https://openalex.org/C541664917","wikidata":"https://www.wikidata.org/wiki/Q14001","display_name":"Malware","level":2,"score":0.5400062799453735},{"id":"https://openalex.org/C157486923","wikidata":"https://www.wikidata.org/wiki/Q1376436","display_name":"String (physics)","level":2,"score":0.46447765827178955},{"id":"https://openalex.org/C44359876","wikidata":"https://www.wikidata.org/wiki/Q5338467","display_name":"Edit distance","level":2,"score":0.43247509002685547},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4128343462944031},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3944114148616791},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3446786403656006},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15095776319503784},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.08640500903129578},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C1862650","wikidata":"https://www.wikidata.org/wiki/Q186005","display_name":"Physical therapy","level":1,"score":0.0},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ntms49979.2021.9432673","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ntms49979.2021.9432673","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 11th IFIP International Conference on New Technologies, Mobility and Security (NTMS)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2209.00783","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2209.00783","pdf_url":"https://arxiv.org/pdf/2209.00783","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:2209.00783","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2209.00783","pdf_url":"https://arxiv.org/pdf/2209.00783","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1647671624","https://openalex.org/W2066792529","https://openalex.org/W2096733369","https://openalex.org/W2888116124","https://openalex.org/W2903350505","https://openalex.org/W2904453117","https://openalex.org/W3005680577","https://openalex.org/W3034978746","https://openalex.org/W3099206234","https://openalex.org/W3107464100","https://openalex.org/W3109894131","https://openalex.org/W6636915900","https://openalex.org/W6754333852","https://openalex.org/W6756868739","https://openalex.org/W6774314701","https://openalex.org/W6779366610"],"related_works":["https://openalex.org/W2017167536","https://openalex.org/W3203141584","https://openalex.org/W2365836197","https://openalex.org/W1965211349","https://openalex.org/W2940176406","https://openalex.org/W2408861063","https://openalex.org/W1966145327","https://openalex.org/W2347513417","https://openalex.org/W2007540612","https://openalex.org/W2054882906"],"abstract_inverted_index":{"Typo-squatting":[0],"domains":[1],"are":[2,68],"a":[3,60,123,126],"common":[4],"cyber-attack":[5],"technique.":[6],"It":[7],"involves":[8],"utilising":[9],"domain":[10,164,167],"names,":[11],"that":[12,87],"exploit":[13],"possible":[14],"typographical":[15,65],"errors":[16,66],"of":[17,100],"commonly":[18],"visited":[19],"domains,":[20],"to":[21,58,70,85,121,125,133,146,162,170],"carry":[22],"out":[23],"malicious":[24],"activities":[25],"such":[26],"as":[27,161],"phishing,":[28],"malware":[29],"installation,":[30],"etc.":[31],"Current":[32],"approaches":[33],"typically":[34],"revolve":[35],"around":[36],"string":[37],"comparison":[38],"algorithms":[39],"like":[40],"the":[41,79,101,151,158,165],"Demaru-Levenschtein":[42],"Distance":[43],"(DLD)":[44],"algorithm.":[45],"Such":[46],"techniques":[47,105],"do":[48],"not":[49],"take":[50,71,88],"into":[51,89],"account":[52,72,90],"keyboard":[53,91],"distance,":[54],"which":[55,82,163],"researchers":[56],"find":[57],"have":[59],"strong":[61],"correlation":[62],"with":[63],"typical":[64],"and":[67,135],"trying":[69],"of.":[73],"In":[74],"this":[75],"paper,":[76],"we":[77,140],"present":[78],"TypoSwype":[80],"framework":[81],"converts":[83],"strings":[84],"images":[86],"location":[92],"innately.":[93],"We":[94],"also":[95,141],"show":[96],"how":[97],"modern":[98],"state":[99],"art":[102],"image":[103],"recognition":[104],"involving":[106],"Convolutional":[107],"Neural":[108],"Networks,":[109],"trained":[110],"via":[111],"either":[112],"Triplet":[113],"Loss":[114],"or":[115],"NT-Xent":[116],"Loss,":[117],"can":[118],"be":[119],"applied":[120],"learn":[122],"mapping":[124],"lower":[127],"dimensional":[128],"space":[129],"where":[130],"distances":[131],"correspond":[132],"image,":[134],"equivalently,":[136],"textual":[137],"similarity.":[138],"Finally,":[139],"demonstrate":[142],"our":[143],"method's":[144],"ability":[145],"improve":[147],"typo-squatting":[148],"detection":[149],"over":[150],"widely":[152],"used":[153],"DLD":[154],"algorithm,":[155],"while":[156],"maintaining":[157],"classification":[159],"accuracy":[160],"input":[166],"was":[168],"attempting":[169],"typo-squat.":[171]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2021-05-24T00:00:00"}
