{"id":"https://openalex.org/W7133361677","doi":"https://doi.org/10.48550/arxiv.2603.01593","title":"PPEDCRF: Privacy-Preserving Enhanced Dynamic CRF for Location-Privacy Protection for Sequence Videos with Minimal Detection Degradation","display_name":"PPEDCRF: Privacy-Preserving Enhanced Dynamic CRF for Location-Privacy Protection for Sequence Videos with Minimal Detection Degradation","publication_year":2026,"publication_date":"2026-03-02","ids":{"openalex":"https://openalex.org/W7133361677","doi":"https://doi.org/10.48550/arxiv.2603.01593"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.01593","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.01593","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.01593","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5127990499","display_name":"Bo Ma","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Ma, Bo","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127924494","display_name":"Jinsong Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Jinsong","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127885170","display_name":"Weiqi Yan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yan, Weiqi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127883538","display_name":"Catherine Shi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shi, Catherine","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5127994667","display_name":"Minh Nguyen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nguyen, Minh","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5127990499"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.34290000796318054,"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":0.34290000796318054,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.13600000739097595,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.11410000175237656,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/conditional-random-field","display_name":"Conditional random field","score":0.8126999735832214},{"id":"https://openalex.org/keywords/global-positioning-system","display_name":"Global Positioning System","score":0.5343999862670898},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.47209998965263367},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.4537999927997589},{"id":"https://openalex.org/keywords/metadata","display_name":"Metadata","score":0.43479999899864197},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4336000084877014},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4268999993801117},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.36640000343322754}],"concepts":[{"id":"https://openalex.org/C152565575","wikidata":"https://www.wikidata.org/wiki/Q1124538","display_name":"Conditional random field","level":2,"score":0.8126999735832214},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7939000129699707},{"id":"https://openalex.org/C60229501","wikidata":"https://www.wikidata.org/wiki/Q18822","display_name":"Global Positioning System","level":2,"score":0.5343999862670898},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5011000037193298},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.48069998621940613},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.47209998965263367},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.4537999927997589},{"id":"https://openalex.org/C93518851","wikidata":"https://www.wikidata.org/wiki/Q180160","display_name":"Metadata","level":2,"score":0.43479999899864197},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4336000084877014},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4268999993801117},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41519999504089355},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.36640000343322754},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3621000051498413},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.35839998722076416},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.35260000824928284},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.35260000824928284},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.33090001344680786},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.329800009727478},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.3093000054359436},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.3052000105381012},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.28459998965263367},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.2777999937534332},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.2766000032424927},{"id":"https://openalex.org/C64869954","wikidata":"https://www.wikidata.org/wiki/Q1859747","display_name":"False positive paradox","level":2,"score":0.27469998598098755},{"id":"https://openalex.org/C2780233690","wikidata":"https://www.wikidata.org/wiki/Q535347","display_name":"Transparency (behavior)","level":2,"score":0.2736999988555908}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.01593","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.01593","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.01593","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.01593","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.7074059844017029}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Dashcam":[0],"videos":[1],"collected":[2],"by":[3,32],"autonomous":[4],"or":[5],"assisted-driving":[6],"systems":[7],"are":[8,22],"increasingly":[9],"shared":[10],"for":[11],"safety":[12],"auditing":[13],"and":[14,39,56,97,120,133,159,172],"model":[15],"improvement.":[16],"Even":[17],"when":[18],"explicit":[19],"GPS":[20],"metadata":[21],"removed,":[23],"an":[24],"attacker":[25],"can":[26],"still":[27],"infer":[28],"the":[29],"recording":[30],"location":[31,99],"matching":[33],"background":[34,75],"visual":[35],"cues":[36],"(e.g.,":[37,148,157],"buildings":[38],"road":[40],"layouts)":[41],"against":[42],"large-scale":[43],"street-view":[44],"imagery.":[45],"This":[46],"paper":[47],"studies":[48],"location-privacy":[49],"leakage":[50],"under":[51],"a":[52,59,88,105,116,122],"background-based":[53],"retrieval":[54,150],"attacker,":[55],"proposes":[57],"PPEDCRF,":[58],"privacy-preserving":[60],"enhanced":[61],"dynamic":[62,89],"conditional":[63],"random":[64],"field":[65],"framework":[66],"that":[67,91,110,127,141],"injects":[68],"calibrated":[69],"perturbations":[70],"only":[71],"into":[72],"inferred":[73],"location-sensitive":[74],"regions":[76,101],"while":[77,152],"preserving":[78],"foreground":[79],"detection":[80,132,155],"utility.":[81],"PPEDCRF":[82,142],"consists":[83],"of":[84],"three":[85],"components:":[86],"(i)":[87],"CRF":[90],"enforces":[92],"temporal":[93],"consistency":[94],"to":[95,115,130],"discover":[96],"track":[98],"sensitive":[100],"across":[102],"frames,":[103],"(ii)":[104],"normalized":[106],"control":[107],"penalty":[108],"(NCP)":[109],"allocates":[111],"perturbation":[112],"strength":[113],"according":[114],"hierarchical":[117],"sensitivity":[118],"model,":[119],"(iii)":[121],"utility-preserving":[123],"noise":[124],"injection":[125],"module":[126],"minimizes":[128],"interference":[129],"object":[131],"segmentation.":[134],"Experiments":[135],"on":[136],"public":[137],"driving":[138],"datasets":[139],"demonstrate":[140],"significantly":[143],"reduces":[144],"location-retrieval":[145],"attack":[146],"success":[147],"Top-k":[149],"accuracy)":[151],"maintaining":[153],"competitive":[154],"performance":[156],"mAP":[158],"segmentation":[160],"metrics)":[161],"compared":[162],"with":[163],"common":[164],"baselines":[165],"such":[166],"as":[167],"global":[168],"noise,":[169],"white-noise":[170],"masking,":[171],"feature-based":[173],"anonymization.":[174],"The":[175],"source":[176],"code":[177],"is":[178],"in":[179],"https://github.com/mabo1215/PPEDCRF.git":[180]},"counts_by_year":[],"updated_date":"2026-03-04T07:09:34.246503","created_date":"2026-03-04T00:00:00"}