{"id":"https://openalex.org/W4285271341","doi":"https://doi.org/10.1109/tifs.2022.3181859","title":"Inferential Separation for Privacy: Irrelevant Statistics and Quantization","display_name":"Inferential Separation for Privacy: Irrelevant Statistics and Quantization","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4285271341","doi":"https://doi.org/10.1109/tifs.2022.3181859"},"language":"en","primary_location":{"id":"doi:10.1109/tifs.2022.3181859","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2022.3181859","pdf_url":null,"source":{"id":"https://openalex.org/S61310614","display_name":"IEEE Transactions on Information Forensics and Security","issn_l":"1556-6013","issn":["1556-6013","1556-6021"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Information Forensics and Security","raw_type":"journal-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/A5053905337","display_name":"Ce Feng","orcid":"https://orcid.org/0000-0003-4261-9170"},"institutions":[{"id":"https://openalex.org/I186143895","display_name":"Lehigh University","ror":"https://ror.org/012afjb06","country_code":"US","type":"education","lineage":["https://openalex.org/I186143895"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ce Feng","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Lehigh University, Bethlehem, PA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Lehigh University, Bethlehem, PA, USA","institution_ids":["https://openalex.org/I186143895"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014965408","display_name":"Parv Venkitasubramaniam","orcid":"https://orcid.org/0000-0002-0999-3331"},"institutions":[{"id":"https://openalex.org/I186143895","display_name":"Lehigh University","ror":"https://ror.org/012afjb06","country_code":"US","type":"education","lineage":["https://openalex.org/I186143895"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Parv Venkitasubramaniam","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Lehigh University, Bethlehem, PA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Lehigh University, Bethlehem, PA, USA","institution_ids":["https://openalex.org/I186143895"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5053905337"],"corresponding_institution_ids":["https://openalex.org/I186143895"],"apc_list":null,"apc_paid":null,"fwci":0.1381,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.45937575,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"17","issue":null,"first_page":"2241","last_page":"2255"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10964","display_name":"Wireless Communication Security Techniques","score":0.9986000061035156,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9979000091552734,"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/computer-science","display_name":"Computer science","score":0.8530197143554688},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.7849062085151672},{"id":"https://openalex.org/keywords/data-stream","display_name":"Data stream","score":0.6825059652328491},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5960440039634705},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.5595424771308899},{"id":"https://openalex.org/keywords/encryption","display_name":"Encryption","score":0.5253835916519165},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.4835088551044464},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4748965799808502},{"id":"https://openalex.org/keywords/obfuscation","display_name":"Obfuscation","score":0.4228609502315521},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.37225112318992615},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.339746356010437},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.284182608127594},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.16749238967895508},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.133037269115448}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8530197143554688},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.7849062085151672},{"id":"https://openalex.org/C2778484313","wikidata":"https://www.wikidata.org/wiki/Q1172540","display_name":"Data stream","level":2,"score":0.6825059652328491},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5960440039634705},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.5595424771308899},{"id":"https://openalex.org/C148730421","wikidata":"https://www.wikidata.org/wiki/Q141090","display_name":"Encryption","level":2,"score":0.5253835916519165},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.4835088551044464},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4748965799808502},{"id":"https://openalex.org/C40305131","wikidata":"https://www.wikidata.org/wiki/Q2616305","display_name":"Obfuscation","level":2,"score":0.4228609502315521},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.37225112318992615},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.339746356010437},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.284182608127594},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.16749238967895508},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.133037269115448},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tifs.2022.3181859","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2022.3181859","pdf_url":null,"source":{"id":"https://openalex.org/S61310614","display_name":"IEEE Transactions on Information Forensics and Security","issn_l":"1556-6013","issn":["1556-6013","1556-6021"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Information Forensics and Security","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3172341145","display_name":null,"funder_award_id":"CCF-1617889","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W123295786","https://openalex.org/W1561257385","https://openalex.org/W1576267150","https://openalex.org/W1622686296","https://openalex.org/W1714669175","https://openalex.org/W1852728451","https://openalex.org/W1880212920","https://openalex.org/W1969748380","https://openalex.org/W1977862970","https://openalex.org/W2012575779","https://openalex.org/W2013000896","https://openalex.org/W2015820424","https://openalex.org/W2030411764","https://openalex.org/W2033092546","https://openalex.org/W2065978712","https://openalex.org/W2072641892","https://openalex.org/W2078139557","https://openalex.org/W2088881802","https://openalex.org/W2101501407","https://openalex.org/W2103230195","https://openalex.org/W2103827633","https://openalex.org/W2106171298","https://openalex.org/W2115758294","https://openalex.org/W2119379703","https://openalex.org/W2130896996","https://openalex.org/W2133380705","https://openalex.org/W2141002933","https://openalex.org/W2143591442","https://openalex.org/W2144052787","https://openalex.org/W2150472020","https://openalex.org/W2159065056","https://openalex.org/W2160533339","https://openalex.org/W2169270135","https://openalex.org/W2169349251","https://openalex.org/W2274307588","https://openalex.org/W2315646428","https://openalex.org/W2538169415","https://openalex.org/W2595058628","https://openalex.org/W2913635334","https://openalex.org/W2962789088","https://openalex.org/W2963446403","https://openalex.org/W2963535017","https://openalex.org/W3098577220","https://openalex.org/W3099739997","https://openalex.org/W3125786278","https://openalex.org/W4250657332","https://openalex.org/W4255372713","https://openalex.org/W6605051479","https://openalex.org/W6631190155","https://openalex.org/W6665928394","https://openalex.org/W6728765567","https://openalex.org/W6785459140"],"related_works":["https://openalex.org/W1658774705","https://openalex.org/W2106570241","https://openalex.org/W2158759979","https://openalex.org/W105155515","https://openalex.org/W2397112807","https://openalex.org/W2958623481","https://openalex.org/W3046869667","https://openalex.org/W2736127210","https://openalex.org/W2107586730","https://openalex.org/W2183287460"],"abstract_inverted_index":{"This":[0,20,123],"work":[1],"presents":[2],"a":[3,145,160],"new":[4,161],"paradigm":[5,21],"for":[6,53,115,144],"protection":[7],"of":[8,28,84,148],"sensitive":[9,51],"inferences":[10,55,65],"drawn":[11,59],"from":[12,60],"data":[13,30,44,78,146],"streams":[14,79],"with":[15],"relevance":[16],"to":[17,25,111,155,179,190],"Internet-of-Things":[18],"(IoT).":[19],"is":[22,109,126,131,153,165],"an":[23],"alternative":[24],"end-to-end":[26],"encryption":[27],"entire":[29],"streams,":[31],"or":[32],"noise-addition":[33],"based":[34,186],"privatization":[35],"mechanisms.":[36],"It":[37],"relies":[38],"on":[39,192],"the":[40,54,70,93,104,116,134,193],"notion":[41],"that":[42,56,76,92,133,167],"raw":[43],"shared":[45],"through":[46],"IoTs":[47],"are":[48,74,177,188],"themselves":[49],"not":[50],"but":[52],"can":[57,98],"be":[58,99],"them,":[61],"and":[62,87,103],"further,":[63],"these":[64],"vary":[66],"much":[67],"slower":[68],"than":[69],"collected":[71],"data.":[72],"Methodologies":[73],"developed":[75],"transform":[77],"into":[80],"two":[81],"parallel":[82],"sub-streams":[83],"minimum":[85],"sufficient":[86,96],"maximal":[88],"irrelevant":[89,107],"statistics,":[90],"such":[91],"sparse":[94],"minimal":[95],"stream":[97,108,139,147],"protected":[100],"using":[101],"encryption,":[102],"high":[105,195],"rate":[106,196],"guaranteed":[110],"provide":[112],"perfect":[113],"privacy":[114],"underlying":[117],"inference":[118,135],"without":[119],"any":[120],"additional":[121],"protection.":[122],"inferential":[124],"separation":[125],"explored":[127],"theoretically,":[128],"where":[129,159,183],"it":[130],"proved":[132],"relevant":[136],"(minimum":[137],"sufficient)":[138],"grows":[140],"as":[141],"<i>O</i>(log":[142],"<i>t</i>)":[143],"length":[149],"<i>t</i>.":[150],"The":[151,174],"approach":[152],"extended":[154],"bandwidth":[156],"constrained":[157],"devices,":[158],"optimal":[162],"quantization":[163],"scheme":[164],"presented":[166,175],"achieves":[168],"maximum":[169],"fidelity":[170],"while":[171],"guaranteeing":[172],"privacy.":[173],"algorithms":[176],"demonstrated":[178],"practical":[180],"IoT":[181],"datasets":[182],"trained":[184],"CNN":[185],"classifiers":[187],"shown":[189],"fail":[191],"unprotected":[194],"stream.":[197]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
