{"id":"https://openalex.org/W7131308787","doi":"https://doi.org/10.71448/bcds2454-4","title":"Formally Private and Learning-Resistant Location and Query Obfuscation for kNN-based Location-Based Services","display_name":"Formally Private and Learning-Resistant Location and Query Obfuscation for kNN-based Location-Based Services","publication_year":2024,"publication_date":"2024-12-30","ids":{"openalex":"https://openalex.org/W7131308787","doi":"https://doi.org/10.71448/bcds2454-4"},"language":null,"primary_location":{"id":"doi:10.71448/bcds2454-4","is_oa":true,"landing_page_url":"https://doi.org/10.71448/bcds2454-4","pdf_url":null,"source":{"id":"https://openalex.org/S7407053757","display_name":"Bulletin of Computer and Data Sciences","issn_l":"3072-2926","issn":["3072-2926"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Bulletin of Computer and Data Sciences","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.71448/bcds2454-4","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5126675878","display_name":"Yajuan Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yajuan Wang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5126734787","display_name":"Kai Shang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kai Shang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.57509843,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"5","issue":"4","first_page":"44","last_page":"59"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9699000120162964,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9699000120162964,"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/T10237","display_name":"Cryptography and Data Security","score":0.009600000455975533,"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.004900000058114529,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/obfuscation","display_name":"Obfuscation","score":0.7347999811172485},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5364999771118164},{"id":"https://openalex.org/keywords/adversary","display_name":"Adversary","score":0.5296000242233276},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5083000063896179},{"id":"https://openalex.org/keywords/query-optimization","display_name":"Query optimization","score":0.4580000042915344},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.44530001282691956},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.44440001249313354},{"id":"https://openalex.org/keywords/differential-privacy","display_name":"Differential privacy","score":0.42829999327659607},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.3937999904155731}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8148000240325928},{"id":"https://openalex.org/C40305131","wikidata":"https://www.wikidata.org/wiki/Q2616305","display_name":"Obfuscation","level":2,"score":0.7347999811172485},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5364999771118164},{"id":"https://openalex.org/C41065033","wikidata":"https://www.wikidata.org/wiki/Q2825412","display_name":"Adversary","level":2,"score":0.5296000242233276},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5083000063896179},{"id":"https://openalex.org/C157692150","wikidata":"https://www.wikidata.org/wiki/Q2919848","display_name":"Query optimization","level":2,"score":0.4580000042915344},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.44530001282691956},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.44440001249313354},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.43540000915527344},{"id":"https://openalex.org/C23130292","wikidata":"https://www.wikidata.org/wiki/Q5275358","display_name":"Differential privacy","level":2,"score":0.42829999327659607},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.3937999904155731},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.37310001254081726},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.34540000557899475},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.3264999985694885},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3158999979496002},{"id":"https://openalex.org/C155292070","wikidata":"https://www.wikidata.org/wiki/Q1198122","display_name":"Location-based service","level":2,"score":0.3084999918937683},{"id":"https://openalex.org/C9679016","wikidata":"https://www.wikidata.org/wiki/Q1417473","display_name":"Principle of maximum entropy","level":2,"score":0.3084000051021576},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.3084000051021576},{"id":"https://openalex.org/C99016210","wikidata":"https://www.wikidata.org/wiki/Q5488129","display_name":"Query expansion","level":2,"score":0.30399999022483826},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.30239999294281006},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.29319998621940613},{"id":"https://openalex.org/C192028432","wikidata":"https://www.wikidata.org/wiki/Q845739","display_name":"Query language","level":2,"score":0.2872999906539917},{"id":"https://openalex.org/C99221444","wikidata":"https://www.wikidata.org/wiki/Q1532069","display_name":"Private information retrieval","level":2,"score":0.2800999879837036},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.26750001311302185},{"id":"https://openalex.org/C171752962","wikidata":"https://www.wikidata.org/wiki/Q255166","display_name":"Kullback\u2013Leibler divergence","level":2,"score":0.2590999901294708},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.2533999979496002},{"id":"https://openalex.org/C2776104089","wikidata":"https://www.wikidata.org/wiki/Q15894079","display_name":"Location awareness","level":2,"score":0.2533000111579895},{"id":"https://openalex.org/C2778334786","wikidata":"https://www.wikidata.org/wiki/Q1586270","display_name":"Variation (astronomy)","level":2,"score":0.25119999051094055},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.2508000135421753}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.71448/bcds2454-4","is_oa":true,"landing_page_url":"https://doi.org/10.71448/bcds2454-4","pdf_url":null,"source":{"id":"https://openalex.org/S7407053757","display_name":"Bulletin of Computer and Data Sciences","issn_l":"3072-2926","issn":["3072-2926"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Bulletin of Computer and Data Sciences","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.71448/bcds2454-4","is_oa":true,"landing_page_url":"https://doi.org/10.71448/bcds2454-4","pdf_url":null,"source":{"id":"https://openalex.org/S7407053757","display_name":"Bulletin of Computer and Data Sciences","issn_l":"3072-2926","issn":["3072-2926"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Bulletin of Computer and Data Sciences","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Location-based":[0],"services":[1],"(LBS)":[2],"routinely":[3],"answer":[4],"k-nearest":[5],"neighbor":[6],"(kNN)":[7],"queries":[8,157],"over":[9,127],"users\u2019":[10],"locations":[11,19,155],"and":[12,20,35,38,61,72,93,124,139,141,148,156,162,177,180,184,198],"points":[13],"of":[14,136,191],"interest,":[15],"but":[16],"revealing":[17],"precise":[18],"query":[21,36,62,98,104,122],"patterns":[22],"poses":[23],"serious":[24],"privacy":[25,41,70,169,176],"risks.":[26],"Existing":[27],"systems":[28],"rely":[29],"largely":[30],"on":[31],"heuristic":[32,196],"dummy":[33,87,197],"generation":[34,88],"fragmentation,":[37],"typically":[39],"argue":[40],"via":[42],"entropy":[43],"or":[44],"attack-specific":[45],"reasoning":[46],"under":[47],"restricted":[48],"adversary":[49],"models.":[50],"In":[51],"this":[52],"paper,":[53],"we":[54,166],"present":[55],"a":[56,83,95,202],"new":[57],"framework":[58],"for":[59,119,206],"location":[60,120],"obfuscation":[63,99],"in":[64,134],"kNN-based":[65],"LBS":[66],"that":[67,90,101,182],"provides":[68],"formal":[69,175],"guarantees":[71,118],"is":[73],"explicitly":[74],"evaluated":[75],"against":[76,144],"modern":[77],"machine-learning-based":[78],"adversaries.":[79],"We":[80,115],"introduce":[81],"Geo-Obfus,":[82],"spatially":[84],"differentially":[85],"private":[86,97],"mechanism":[89],"satisfies":[91],"geo-indistinguishability,":[92],"Query-Obfus,":[94],"distributionally":[96],"scheme":[100],"protects":[102],"sensitive":[103],"attributes,":[105],"both":[106],"integrated":[107],"into":[108],"an":[109],"efficient":[110],"two-stage":[111],"kNN":[112,137,178,208],"processing":[113],"pipeline.":[114],"derive":[116],"theoretical":[117],"privacy,":[121,123],"their":[125],"composition":[126],"repeated":[128],"queries,":[129],"analyze":[130],"the":[131,172,188],"utility":[132,179],"loss":[133],"terms":[135],"accuracy":[138],"latency,":[140],"evaluate":[142],"robustness":[143],"optimal":[145],"Bayesian":[146],"inference":[147],"neural":[149],"classifiers":[150],"trained":[151],"to":[152],"distinguish":[153],"real":[154,161],"from":[158],"dummies.":[159],"Using":[160],"synthetic":[163],"mobility":[164],"datasets,":[165],"show":[167],"how":[168],"parameters":[170],"control":[171],"trade-off":[173],"between":[174],"demonstrate":[181],"Geo-Obfus":[183],"Query-Obfus":[185],"substantially":[186],"reduce":[187],"success":[189],"rate":[190],"learning-based":[192],"attacks":[193],"compared":[194],"with":[195],"fragmentation":[199],"methods,":[200],"providing":[201],"principled,":[203],"learning-resistant":[204],"foundation":[205],"privacy-preserving":[207],"services.":[209]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-02-25T00:00:00"}
