{"id":"https://openalex.org/W4415124583","doi":"https://doi.org/10.1109/icmlt65785.2025.11193248","title":"Enhancing Android Lock Pattern Security with Personalized Federated Learning and Multi-Modal Framework","display_name":"Enhancing Android Lock Pattern Security with Personalized Federated Learning and Multi-Modal Framework","publication_year":2025,"publication_date":"2025-05-23","ids":{"openalex":"https://openalex.org/W4415124583","doi":"https://doi.org/10.1109/icmlt65785.2025.11193248"},"language":"en","primary_location":{"id":"doi:10.1109/icmlt65785.2025.11193248","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmlt65785.2025.11193248","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 10th International Conference on Machine Learning Technologies (ICMLT)","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/A5113119101","display_name":"Sina Apak","orcid":null},"institutions":[{"id":"https://openalex.org/I179948855","display_name":"Istanbul Ayd\u0131n University","ror":"https://ror.org/00qsyw664","country_code":"TR","type":"education","lineage":["https://openalex.org/I179948855"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Sina Apak","raw_affiliation_strings":["Istanbul Aydin University,Dept. of Management Information Technology,Istanbul,Türkiye"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Istanbul Aydin University,Dept. of Management Information Technology,Istanbul,Türkiye","institution_ids":["https://openalex.org/I179948855"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112968278","display_name":"Peri G\u00fcne\u015f","orcid":null},"institutions":[{"id":"https://openalex.org/I179948855","display_name":"Istanbul Ayd\u0131n University","ror":"https://ror.org/00qsyw664","country_code":"TR","type":"education","lineage":["https://openalex.org/I179948855"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Peri G\u00fcne\u015f","raw_affiliation_strings":["Istanbul Aydin University,Dept. of Management Information Technology,Istanbul,Türkiye"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Istanbul Aydin University,Dept. of Management Information Technology,Istanbul,Türkiye","institution_ids":["https://openalex.org/I179948855"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I179948855"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"223","last_page":"232"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9725000262260437,"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":0.9725000262260437,"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/T12222","display_name":"IoT-based Smart Home Systems","score":0.9524000287055969,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"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":0.9275000095367432,"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/android","display_name":"Android (operating system)","score":0.5651000142097473},{"id":"https://openalex.org/keywords/adaptability","display_name":"Adaptability","score":0.5198000073432922},{"id":"https://openalex.org/keywords/android-malware","display_name":"Android malware","score":0.4661000072956085},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.42980000376701355},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.41449999809265137},{"id":"https://openalex.org/keywords/personalization","display_name":"Personalization","score":0.39329999685287476},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.3831999897956848},{"id":"https://openalex.org/keywords/malware","display_name":"Malware","score":0.38109999895095825},{"id":"https://openalex.org/keywords/intrusion-detection-system","display_name":"Intrusion detection system","score":0.3646000027656555}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7479000091552734},{"id":"https://openalex.org/C557433098","wikidata":"https://www.wikidata.org/wiki/Q94","display_name":"Android (operating system)","level":2,"score":0.5651000142097473},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.5198000073432922},{"id":"https://openalex.org/C2989133298","wikidata":"https://www.wikidata.org/wiki/Q94","display_name":"Android malware","level":3,"score":0.4661000072956085},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.42980000376701355},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.41839998960494995},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.41449999809265137},{"id":"https://openalex.org/C183003079","wikidata":"https://www.wikidata.org/wiki/Q1000371","display_name":"Personalization","level":2,"score":0.39329999685287476},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.3831999897956848},{"id":"https://openalex.org/C541664917","wikidata":"https://www.wikidata.org/wiki/Q14001","display_name":"Malware","level":2,"score":0.38109999895095825},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37770000100135803},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.3646000027656555},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.36230000853538513},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.36160001158714294},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32749998569488525},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.3273000121116638},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.3160000145435333},{"id":"https://openalex.org/C93996380","wikidata":"https://www.wikidata.org/wiki/Q44127","display_name":"Server","level":2,"score":0.3093000054359436},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.3068999946117401},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.2953000068664551},{"id":"https://openalex.org/C2776743756","wikidata":"https://www.wikidata.org/wiki/Q5097921","display_name":"Safeguarding","level":2,"score":0.2930000126361847},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.29030001163482666},{"id":"https://openalex.org/C174839445","wikidata":"https://www.wikidata.org/wiki/Q1134386","display_name":"Lock (firearm)","level":2,"score":0.28790000081062317},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.2847999930381775},{"id":"https://openalex.org/C202477664","wikidata":"https://www.wikidata.org/wiki/Q1352449","display_name":"Client-side","level":2,"score":0.2777999937534332},{"id":"https://openalex.org/C178005623","wikidata":"https://www.wikidata.org/wiki/Q308859","display_name":"Anonymity","level":2,"score":0.27709999680519104},{"id":"https://openalex.org/C48105269","wikidata":"https://www.wikidata.org/wiki/Q1141160","display_name":"Header","level":2,"score":0.2761000096797943},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.26969999074935913},{"id":"https://openalex.org/C522325796","wikidata":"https://www.wikidata.org/wiki/Q471880","display_name":"Identity theft","level":2,"score":0.25609999895095825},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.25540000200271606},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2549999952316284},{"id":"https://openalex.org/C148417208","wikidata":"https://www.wikidata.org/wiki/Q4825882","display_name":"Authentication (law)","level":2,"score":0.25220000743865967}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icmlt65785.2025.11193248","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmlt65785.2025.11193248","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 10th International Conference on Machine Learning Technologies (ICMLT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1997833177","https://openalex.org/W2164940355","https://openalex.org/W2740839773","https://openalex.org/W2902911557","https://openalex.org/W2973508239","https://openalex.org/W2973589623","https://openalex.org/W3105429705","https://openalex.org/W3207903161","https://openalex.org/W3210231570","https://openalex.org/W4298111208","https://openalex.org/W4323644357","https://openalex.org/W4366266301","https://openalex.org/W4378364326","https://openalex.org/W4379662090","https://openalex.org/W4386435074","https://openalex.org/W4388691996","https://openalex.org/W4389459265","https://openalex.org/W4390738456","https://openalex.org/W4393144919","https://openalex.org/W4393254875","https://openalex.org/W4396912095","https://openalex.org/W4399386664","https://openalex.org/W4399449845","https://openalex.org/W4399453076","https://openalex.org/W4400192394","https://openalex.org/W4401096216","https://openalex.org/W4401115759","https://openalex.org/W4401634195","https://openalex.org/W4401669769","https://openalex.org/W4402291894","https://openalex.org/W4402567580","https://openalex.org/W4402634413","https://openalex.org/W4402642373","https://openalex.org/W4403378445","https://openalex.org/W4403680045","https://openalex.org/W4404016449","https://openalex.org/W4404095747","https://openalex.org/W4404579677"],"related_works":[],"abstract_inverted_index":{"The":[0,70,218],"Android":[1,47,214,257],"Lock":[2],"Pattern":[3],"is":[4,20,53],"a":[5,82,99,126,247],"popular":[6],"authentication":[7,18,258],"technique":[8,120],"because":[9],"of":[10,74,153,181,189,223,236],"its":[11,230],"simplicity,":[12],"ease,":[13],"and":[14,30,45,66,97,184,195,244,249],"security.":[15],"Nonetheless,":[16],"this":[17],"mechanism":[19],"vulnerable":[21],"to":[22,41,111,124,149,226,252],"several":[23],"attacks":[24],"including":[25],"man-in-the-middle":[26,62],"(MITM)":[27,63],"attacks,":[28,64,198],"spoofing,":[29,65],"identity":[31,67],"impersonation.":[32],"This":[33,51,139],"study":[34],"presents":[35],"an":[36,221],"innovative":[37],"multimodal":[38,117,177],"framework":[39,72,219],"designed":[40],"detect":[42],"anomalous":[43],"behaviors":[44,152],"fortify":[46],"lock":[48,113,193],"pattern":[49,114],"authentication.":[50],"method":[52,140],"highly":[54],"effective":[55],"in":[56,176,206,232,256],"countering":[57],"advanced":[58],"threats":[59,209,255],"such":[60],"as":[61],"impersonation":[68],"attempts.":[69],"proposed":[71],"consists":[73],"two":[75],"core":[76],"components":[77],"that":[78,89,107],"work":[79],"together:":[80],"(1)":[81],"Long":[83],"Short-Term":[84],"Memory":[85],"(LSTM)":[86],"attention":[87],"autoencoder":[88],"analyzes":[90],"network":[91],"traffic":[92],"for":[93,129,186],"abnormal":[94],"timing":[95],"patterns":[96],"(2)":[98],"Neural":[100],"Architecture":[101],"Search":[102],"(NAS)":[103],"optimized":[104],"MobileNetV3":[105],"model":[106,147,163],"l":[108],"generates":[109],"heatmaps":[110],"capture":[112],"characteristics.":[115],"A":[116],"deep":[118],"learning":[119],"fuses":[121],"these":[122],"features":[123],"create":[125],"unique":[127],"profile":[128],"each":[130,166],"individual":[131,154],"within":[132],"the":[133,150,172,187,203,211,241],"personalized":[134],"Federated":[135],"Learning":[136],"(PFL)":[137],"framework.":[138],"improves":[141],"anomaly":[142],"detection":[143,188],"precision":[144],"by":[145],"tailoring":[146],"training":[148,164],"specific":[151],"clients":[155],"while":[156],"concurrently":[157],"safeguarding":[158],"data":[159],"privacy":[160],"via":[161],"localized":[162],"on":[165],"client's":[167],"device.":[168],"Experimental":[169],"results":[170,239],"prove":[171],"framework's":[173,204,242],"exceptional":[174],"performance":[175],"settings,":[178],"achieving":[179],"accuracies":[180],"99.17%,":[182],"97.0%,":[183],"99.0%":[185],"touch":[190],"logging,":[191],"fake":[192],"screens,":[194],"shoulder":[196],"surfing":[197],"respectively.":[199],"Furthermore,":[200],"we":[201],"evaluated":[202],"efficacy":[205],"recognizing":[207],"software-based":[208],"using":[210],"CICMalDroid":[212],"2020":[213],"malware":[215],"public":[216],"dataset.":[217],"achieved":[220],"accuracy":[222],"98.0%,":[224],"comparable":[225],"state-of-the-art":[227],"algorithms,":[228],"demonstrating":[229],"adaptability":[231],"tackling":[233],"various":[234],"types":[235],"threats.":[237],"These":[238],"highlight":[240],"robustness":[243],"scalability,":[245],"offering":[246],"comprehensive":[248],"adaptable":[250],"solution":[251],"emerging":[253],"security":[254],"systems.":[259]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-14T00:00:00"}