{"id":"https://openalex.org/W1987717995","doi":"https://doi.org/10.1109/bigdata.2014.7004384","title":"Location prediction attacks using tensor factorization and optimal defenses","display_name":"Location prediction attacks using tensor factorization and optimal defenses","publication_year":2014,"publication_date":"2014-10-01","ids":{"openalex":"https://openalex.org/W1987717995","doi":"https://doi.org/10.1109/bigdata.2014.7004384","mag":"1987717995"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata.2014.7004384","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2014.7004384","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},"type":"article","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/A5085794030","display_name":"Takao Murakami","orcid":"https://orcid.org/0000-0002-5110-1261"},"institutions":[{"id":"https://openalex.org/I73613424","display_name":"National Institute of Advanced Industrial Science and Technology","ror":"https://ror.org/01703db54","country_code":"JP","type":"government","lineage":["https://openalex.org/I73613424"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takao Murakami","raw_affiliation_strings":["Research Institute for Secure Systems (RISEC), National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki, Japan","Research Institute for Secure Systems (RISEC), National Institute of Advanced Industrial Science and Technology (AIST) Tsukuba Central 2, 1-1-1 Umezono, Tsukuba, Ibaraki, 305-8568, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research Institute for Secure Systems (RISEC), National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki, Japan","institution_ids":["https://openalex.org/I73613424"]},{"raw_affiliation_string":"Research Institute for Secure Systems (RISEC), National Institute of Advanced Industrial Science and Technology (AIST) Tsukuba Central 2, 1-1-1 Umezono, Tsukuba, Ibaraki, 305-8568, Japan","institution_ids":["https://openalex.org/I73613424"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055678870","display_name":"Hajime Watanabe","orcid":"https://orcid.org/0000-0002-0011-1638"},"institutions":[{"id":"https://openalex.org/I73613424","display_name":"National Institute of Advanced Industrial Science and Technology","ror":"https://ror.org/01703db54","country_code":"JP","type":"government","lineage":["https://openalex.org/I73613424"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hajime Watanabe","raw_affiliation_strings":["Research Institute for Secure Systems (RISEC), National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki, Japan","Research Institute for Secure Systems (RISEC), National Institute of Advanced Industrial Science and Technology (AIST) Tsukuba Central 2, 1-1-1 Umezono, Tsukuba, Ibaraki, 305-8568, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research Institute for Secure Systems (RISEC), National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki, Japan","institution_ids":["https://openalex.org/I73613424"]},{"raw_affiliation_string":"Research Institute for Secure Systems (RISEC), National Institute of Advanced Industrial Science and Technology (AIST) Tsukuba Central 2, 1-1-1 Umezono, Tsukuba, Ibaraki, 305-8568, Japan","institution_ids":["https://openalex.org/I73613424"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3515,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.56289979,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"13","last_page":"21"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"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":0.9952999949455261,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9904000163078308,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7638109922409058},{"id":"https://openalex.org/keywords/stochastic-matrix","display_name":"Stochastic matrix","score":0.6185666918754578},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.5903147459030151},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.5876286029815674},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5805454850196838},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.5609919428825378},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5447689890861511},{"id":"https://openalex.org/keywords/non-negative-matrix-factorization","display_name":"Non-negative matrix factorization","score":0.49622565507888794},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.47289004921913147},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.46450895071029663},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4485102593898773},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.42797422409057617},{"id":"https://openalex.org/keywords/factorization","display_name":"Factorization","score":0.41616925597190857},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3953450322151184},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3826673626899719},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3626006245613098},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2889094948768616},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14949864149093628}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7638109922409058},{"id":"https://openalex.org/C49555168","wikidata":"https://www.wikidata.org/wiki/Q176583","display_name":"Stochastic matrix","level":3,"score":0.6185666918754578},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.5903147459030151},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.5876286029815674},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5805454850196838},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.5609919428825378},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5447689890861511},{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.49622565507888794},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.47289004921913147},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.46450895071029663},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4485102593898773},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.42797422409057617},{"id":"https://openalex.org/C187834632","wikidata":"https://www.wikidata.org/wiki/Q188804","display_name":"Factorization","level":2,"score":0.41616925597190857},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3953450322151184},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3826673626899719},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3626006245613098},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2889094948768616},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14949864149093628},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata.2014.7004384","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2014.7004384","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5299999713897705,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1246381107","https://openalex.org/W1548445892","https://openalex.org/W1582429829","https://openalex.org/W1890688605","https://openalex.org/W1914599625","https://openalex.org/W1974653074","https://openalex.org/W1981512030","https://openalex.org/W1993823777","https://openalex.org/W2009225057","https://openalex.org/W2023751717","https://openalex.org/W2024165284","https://openalex.org/W2054141820","https://openalex.org/W2073684569","https://openalex.org/W2080206036","https://openalex.org/W2089349245","https://openalex.org/W2089554252","https://openalex.org/W2120911939","https://openalex.org/W2125838338","https://openalex.org/W2127394876","https://openalex.org/W2165804980","https://openalex.org/W2171279286","https://openalex.org/W2260906342","https://openalex.org/W2612623515","https://openalex.org/W2769353087","https://openalex.org/W2799061466","https://openalex.org/W4205687621","https://openalex.org/W4297787516","https://openalex.org/W6639683144"],"related_works":["https://openalex.org/W2127243424","https://openalex.org/W4390394189","https://openalex.org/W2037504162","https://openalex.org/W2539013788","https://openalex.org/W2792706544","https://openalex.org/W1568451138","https://openalex.org/W2156699640","https://openalex.org/W2045265907","https://openalex.org/W2972997031","https://openalex.org/W2075222291"],"abstract_inverted_index":{"Recent":[0],"studies":[1],"have":[2],"proposed":[3],"various":[4],"attacks":[5],"against":[6,62],"location":[7,30,109,115,123],"privacy":[8],"using":[9,145],"a":[10,21,26,74,79,85,97,108,114,117,121,129],"Markov":[11],"Chain":[12],"transition":[13,82,94,177],"matrix":[14],"trained":[15],"for":[16],"each":[17],"user.":[18],"However,":[19],"when":[20,169],"user":[22,119],"has":[23,172],"disclosed":[24],"only":[25],"small":[27,98],"amount":[28,99],"of":[29,65,81,100,116,148,154],"information":[31],"in":[32],"the":[33,35,48,58,135,146,152,170],"past,":[34],"training":[36,75,101],"data":[37,54],"can":[38,50,60],"be":[39],"extremely":[40],"sparse.":[41],"In":[42],"this":[43,52,63],"paper,":[44],"we":[45],"show":[46,151],"how":[47,57],"attacker":[49],"solve":[51],"sparse":[53],"problem,":[55],"and":[56,87,127],"defender":[59,171],"defend":[61],"type":[64],"attack.":[66],"Our":[67],"proposal":[68],"is":[69,166],"twofold:":[70],"1)":[71],"We":[72,104,157],"propose":[73,128],"method":[76,132,165],"that":[77,124,161],"regards":[78],"set":[80],"matrices":[83,95],"as":[84,138],"\u201ctensor\u201d,":[86],"adopt":[88],"tensor":[89],"factorization":[90],"to":[91,133,175],"robustly":[92],"estimate":[93],"from":[96,120],"data.":[102],"2)":[103],"then":[105],"focus":[106],"on":[107],"prediction":[110],"attack,":[111],"which":[112],"predicts":[113],"target":[118],"past":[122],"he/she":[125],"disclosed,":[126],"region":[130,136,163],"merging":[131,164],"minimize":[134],"size":[137],"an":[139],"optimal":[140],"defense.":[141],"The":[142],"experimental":[143],"results":[144],"dataset":[147],"taxi":[149],"traces":[150],"effectiveness":[153],"our":[155,162],"proposals.":[156],"also":[158],"point":[159],"out":[160],"effective":[167],"especially":[168],"Big":[173],"Data":[174],"train":[176],"matrices.":[178]},"counts_by_year":[{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}