{"id":"https://openalex.org/W3114976675","doi":"https://doi.org/10.1109/isncc49221.2020.9297188","title":"Human Trait Analysis via Machine Learning Techniques for User Authentication","display_name":"Human Trait Analysis via Machine Learning Techniques for User Authentication","publication_year":2020,"publication_date":"2020-10-20","ids":{"openalex":"https://openalex.org/W3114976675","doi":"https://doi.org/10.1109/isncc49221.2020.9297188","mag":"3114976675"},"language":"en","primary_location":{"id":"doi:10.1109/isncc49221.2020.9297188","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isncc49221.2020.9297188","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Symposium on Networks, Computers and Communications (ISNCC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5088261252","display_name":"Iman I. M. Abu Sulayman","orcid":"https://orcid.org/0000-0002-2508-1746"},"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":"Iman I. M. Abu Sulayman","raw_affiliation_strings":["Western University, London, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Western University, London, Canada","institution_ids":["https://openalex.org/I125749732"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037757429","display_name":"Abdelkader Ouda","orcid":"https://orcid.org/0000-0003-3882-1763"},"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":"Abdelkader Ouda","raw_affiliation_strings":["Western University, London, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Western University, London, 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":0.345,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.60718518,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9983000159263611,"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":0.9983000159263611,"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":0.9975000023841858,"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/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9965999722480774,"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/computer-science","display_name":"Computer science","score":0.7965959310531616},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6826408505439758},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.6273485422134399},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6182887554168701},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5873475670814514},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.47198325395584106},{"id":"https://openalex.org/keywords/intrusion-detection-system","display_name":"Intrusion detection system","score":0.41508686542510986},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.39812007546424866}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7965959310531616},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6826408505439758},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.6273485422134399},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6182887554168701},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5873475670814514},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.47198325395584106},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.41508686542510986},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39812007546424866},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isncc49221.2020.9297188","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isncc49221.2020.9297188","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Symposium on Networks, Computers and Communications (ISNCC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.7799999713897705,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W1602378003","https://openalex.org/W1970984514","https://openalex.org/W1972893535","https://openalex.org/W2001836602","https://openalex.org/W2012973816","https://openalex.org/W2016081440","https://openalex.org/W2025164705","https://openalex.org/W2033508598","https://openalex.org/W2070396449","https://openalex.org/W2071348259","https://openalex.org/W2074209220","https://openalex.org/W2076245464","https://openalex.org/W2094205093","https://openalex.org/W2155272489","https://openalex.org/W2337453828","https://openalex.org/W2345301719","https://openalex.org/W2492102116","https://openalex.org/W2513503470","https://openalex.org/W2543401363","https://openalex.org/W2553036665","https://openalex.org/W2557338026","https://openalex.org/W2559819687","https://openalex.org/W2636839313","https://openalex.org/W2712153609","https://openalex.org/W2724553162","https://openalex.org/W2737110920","https://openalex.org/W2765884627","https://openalex.org/W2766307113","https://openalex.org/W2766846559","https://openalex.org/W2774497477","https://openalex.org/W2783176580","https://openalex.org/W2786746809","https://openalex.org/W2795147830","https://openalex.org/W2795352943","https://openalex.org/W2797283471","https://openalex.org/W2807998075","https://openalex.org/W2907662800","https://openalex.org/W2908621704","https://openalex.org/W2913790915","https://openalex.org/W2919816726","https://openalex.org/W2945177111","https://openalex.org/W2952460830","https://openalex.org/W2962849408","https://openalex.org/W2963142780","https://openalex.org/W2963672374","https://openalex.org/W2964581798","https://openalex.org/W2972498781","https://openalex.org/W2976507397","https://openalex.org/W2995175434","https://openalex.org/W4249837478"],"related_works":["https://openalex.org/W2053269318","https://openalex.org/W2364370872","https://openalex.org/W2097963413","https://openalex.org/W2025614924","https://openalex.org/W2294335174","https://openalex.org/W3145575561","https://openalex.org/W2364419519","https://openalex.org/W2360767377","https://openalex.org/W2017948608","https://openalex.org/W2360951146"],"abstract_inverted_index":{"Machine":[0],"learning":[1,177],"is":[2,38,134,150,170],"an":[3,113],"extremely":[4],"important":[5],"technique":[6,115,133,169],"that":[7,43,104,120],"has":[8],"become":[9],"heavily":[10],"used":[11],"in":[12,76,135,202,225,243],"different":[13],"types":[14],"of":[15,41,68,89,100,131,138,144,166,175,207,228,239],"applications":[16],"such":[17,81],"as":[18,82],"detection":[19],"systems":[20,28],"for":[21,29,48,116,124],"fraud,":[22],"intrusion":[23],"or":[24,31],"fault":[25],"and":[26,36,73,84,141,164,178,194,219],"monitoring":[27],"health":[30],"computer.":[32],"Human":[33,51],"trait":[34,52,118],"analysis":[35,53,95,119,163],"identification":[37,60],"a":[39,45,55,216,221],"field":[40],"research":[42],"needs":[44,123],"strong":[46],"implementation":[47],"machine":[49,176],"learning.":[50],"provides":[54],"tool":[56],"with":[57],"which":[58],"human":[59,69,105,117],"factors":[61],"can":[62,107],"be":[63,108],"verified.":[64],"Currently,":[65],"detail":[66],"aspects":[67],"behavior":[70],"are":[71,233],"digitally":[72],"continuously":[74],"logged":[75],"Big":[77],"Data":[78],"based":[79,171,182],"platforms":[80],"Twitter":[83],"Facebook.":[85],"This":[86,110],"continuous":[87],"flow":[88],"high-volume":[90],"data":[91,94,162],"requires":[92],"sophisticated":[93],"to":[96,152,156,235],"examine":[97],"huge":[98],"amounts":[99],"behavioral":[101],"evidence":[102],"so":[103],"traits":[106],"modeled.":[109],"paper":[111],"proposes":[112],"innovative":[114],"fits":[121],"the":[122,136,139,145,148,167,173,237],"user's":[125],"identity":[126],"verification.":[127],"The":[128,161],"pioneering":[129],"work":[130],"this":[132],"distinction":[137],"normal":[140],"abnormal":[142,154],"actions":[143,155],"users,":[146],"where":[147],"focus":[149],"given":[151],"these":[153,240],"establish":[157],"security":[158,212],"potential":[159,213],"profiles.":[160],"prediction":[165,206],"proposed":[168],"on":[172,183],"concept":[174],"uses":[179],"several":[180],"models":[181],"four":[184,203],"techniques;":[185],"K-means,":[186],"Hidden":[187],"Markov":[188],"Model":[189],"(HMM),":[190],"Auto-Encoder":[191],"Neural":[192],"Network,":[193],"Gaussian":[195],"Distribution.":[196],"Experiments":[197],"have":[198],"been":[199],"carried":[200],"out":[201],"main":[204],"phases:":[205],"rare":[208],"user":[209,217,247],"actions,":[210,214],"filter":[211],"build/update":[215],"profile,":[218],"generate":[220],"real-time":[222],"(i.e.":[223],"just":[224],"time)":[226],"set":[227],"challenging":[229,241],"questions.":[230],"Real-world":[231],"scenarios":[232],"considered":[234],"demonstrate":[236],"benefits":[238],"questions":[242],"building":[244],"secure":[245],"knowledge-based":[246],"authentication":[248],"systems.":[249]},"counts_by_year":[{"year":2022,"cited_by_count":3}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}