{"id":"https://openalex.org/W2911853677","doi":"https://doi.org/10.1109/bigdata.2018.8622372","title":"DeepFP: A Deep Learning Framework For User Fingerprinting via Mobile Motion Sensors","display_name":"DeepFP: A Deep Learning Framework For User Fingerprinting via Mobile Motion Sensors","publication_year":2018,"publication_date":"2018-12-01","ids":{"openalex":"https://openalex.org/W2911853677","doi":"https://doi.org/10.1109/bigdata.2018.8622372","mag":"2911853677"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata.2018.8622372","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2018.8622372","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Big Data (Big Data)","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/A5058324329","display_name":"Sara Amini","orcid":null},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sara Amini","raw_affiliation_strings":["Department of Computer Science, University of Illinois, Chicago, IL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Illinois, Chicago, IL, USA","institution_ids":["https://openalex.org/I39422238"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005843015","display_name":"Vahid Noroozi","orcid":null},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vahid Noroozi","raw_affiliation_strings":["Department of Computer Science, University of Illinois, Chicago, IL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Illinois, Chicago, IL, USA","institution_ids":["https://openalex.org/I39422238"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059877468","display_name":"Sara Bahaadini","orcid":null},"institutions":[{"id":"https://openalex.org/I111979921","display_name":"Northwestern University","ror":"https://ror.org/000e0be47","country_code":"US","type":"education","lineage":["https://openalex.org/I111979921"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sara Bahaadini","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, Northwestern University, IL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, Northwestern University, IL, USA","institution_ids":["https://openalex.org/I111979921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036357902","display_name":"Philip S. Yu","orcid":"https://orcid.org/0000-0002-3491-5968"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Philip S. Yu","raw_affiliation_strings":["Department of Computer Science, University of Illinois, Chicago, IL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Illinois, Chicago, IL, USA","institution_ids":["https://openalex.org/I39422238"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070578895","display_name":"Chris Kanich","orcid":"https://orcid.org/0000-0002-3836-2168"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chris Kanich","raw_affiliation_strings":["Department of Computer Science, University of Illinois, Chicago, IL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Illinois, Chicago, IL, USA","institution_ids":["https://openalex.org/I39422238"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3042,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.68873952,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"9","issue":null,"first_page":"84","last_page":"91"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9994999766349792,"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"}},"topics":[{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9994999766349792,"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"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.996999979019165,"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/T11800","display_name":"User Authentication and Security Systems","score":0.9957000017166138,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.822831928730011},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6786558628082275},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6465153694152832},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6225330829620361},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6187183260917664},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.6012158393859863},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5779604315757751},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.5765617489814758},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.562908947467804},{"id":"https://openalex.org/keywords/mobile-device","display_name":"Mobile device","score":0.487605482339859},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.479845255613327},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4586174488067627},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.4501304030418396},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09584683179855347},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.08810919523239136},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.08234009146690369}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.822831928730011},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6786558628082275},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6465153694152832},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6225330829620361},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6187183260917664},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.6012158393859863},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5779604315757751},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.5765617489814758},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.562908947467804},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.487605482339859},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.479845255613327},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4586174488067627},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.4501304030418396},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09584683179855347},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.08810919523239136},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.08234009146690369},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata.2018.8622372","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2018.8622372","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.7300000190734863,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W47803021","https://openalex.org/W581956982","https://openalex.org/W1480487340","https://openalex.org/W1483327747","https://openalex.org/W1522301498","https://openalex.org/W1525967479","https://openalex.org/W1663973292","https://openalex.org/W1861537833","https://openalex.org/W1981029888","https://openalex.org/W2000275092","https://openalex.org/W2016589492","https://openalex.org/W2017658349","https://openalex.org/W2038790378","https://openalex.org/W2062118960","https://openalex.org/W2064675550","https://openalex.org/W2066372561","https://openalex.org/W2076434944","https://openalex.org/W2079259462","https://openalex.org/W2135346934","https://openalex.org/W2187089797","https://openalex.org/W2293480925","https://openalex.org/W2297075900","https://openalex.org/W2405765445","https://openalex.org/W2409587536","https://openalex.org/W2553915786","https://openalex.org/W2594639291","https://openalex.org/W2807329228","https://openalex.org/W2896561506","https://openalex.org/W2964121744","https://openalex.org/W2964131555","https://openalex.org/W2964198128","https://openalex.org/W3102407811","https://openalex.org/W4293334322","https://openalex.org/W4295023194","https://openalex.org/W6602024816","https://openalex.org/W6616837769","https://openalex.org/W6631190155","https://openalex.org/W6697167593","https://openalex.org/W6843086162"],"related_works":["https://openalex.org/W17155033","https://openalex.org/W3207760230","https://openalex.org/W1496222301","https://openalex.org/W4312814274","https://openalex.org/W1590307681","https://openalex.org/W2536018345","https://openalex.org/W4285370786","https://openalex.org/W2296488620","https://openalex.org/W2358353312","https://openalex.org/W2353836703"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"propose":[4],"a":[5,99,138,145,153],"deep":[6,73],"learning":[7,35,70],"framework":[8],"for":[9,37],"user":[10,38,82],"fingerprinting":[11],"via":[12],"mobile":[13,156],"motion":[14],"sensors,":[15],"DeepFP,":[16],"which":[17,126],"can":[18],"identify":[19,123],"and":[20,42,72,94,159],"track":[21],"users":[22,61,125],"based":[23],"on":[24,58,152],"their":[25],"behavioral":[26],"patterns":[27],"while":[28],"interacting":[29],"with":[30,137,161],"the":[31,60,78,111,166],"smartphone.":[32],"Existing":[33],"machine":[34],"techniques":[36,71],"identification":[39,83],"are":[40,44,107],"classification-oriented":[41],"thus":[43],"not":[45,118],"amenable":[46],"easily":[47],"to":[48,55,65,76,89,98,109,120,122,130],"large-scale,":[49],"real":[50,134],"world":[51,135],"deployment.":[52],"They":[53],"need":[54,119],"be":[56,131],"trained":[57],"all":[59],"whom":[62],"they":[63],"want":[64],"identify.":[66],"DeepFP":[67,116],"exploits":[68],"metric":[69],"neural":[74,105],"networks":[75,106],"address":[77],"challenges":[79],"of":[80,114,141,148,168],"current":[81],"techniques.":[84],"We":[85],"leverage":[86],"feature":[87],"embedding":[88,163],"directly":[90],"extract":[91],"informative":[92],"features":[93],"map":[95],"input":[96],"samples":[97],"discriminative":[100],"lower-dimensional":[101],"space,":[102],"where":[103],"recurrent":[104],"used":[108,132],"model":[110],"temporal":[112],"information":[113],"data.":[115],"does":[117],"re-train":[121],"new":[124],"makes":[127],"it":[128],"feasible":[129],"in":[133],"scenarios":[136],"huge":[139],"number":[140,147],"users,":[142],"without":[143],"needing":[144],"large":[146],"training":[149],"samples.":[150],"Experiments":[151],"publicly":[154],"available":[155],"sensors":[157],"dataset":[158],"comparison":[160],"other":[162],"methods":[164],"depict":[165],"effectiveness":[167],"DeepFP.":[169]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2019,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}