{"id":"https://openalex.org/W3173424199","doi":"https://doi.org/10.1109/itw46852.2021.9457602","title":"Measuring Information Leakage in Non-stochastic Brute-Force Guessing","display_name":"Measuring Information Leakage in Non-stochastic Brute-Force Guessing","publication_year":2021,"publication_date":"2021-04-11","ids":{"openalex":"https://openalex.org/W3173424199","doi":"https://doi.org/10.1109/itw46852.2021.9457602","mag":"3173424199"},"language":"en","primary_location":{"id":"doi:10.1109/itw46852.2021.9457602","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itw46852.2021.9457602","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Information Theory Workshop (ITW)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://hdl.handle.net/11343/278811","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5068636477","display_name":"Farhad Farokhi","orcid":"https://orcid.org/0000-0002-5102-7073"},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Farhad Farokhi","raw_affiliation_strings":["The University of Melbourne,Department of Electrical and Electronic Engineering,Parkville,Australia","Department of Electrical and Electronic Engineering, The University of Melbourne, Parkville, Australia"],"affiliations":[{"raw_affiliation_string":"The University of Melbourne,Department of Electrical and Electronic Engineering,Parkville,Australia","institution_ids":["https://openalex.org/I165779595"]},{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, The University of Melbourne, Parkville, Australia","institution_ids":["https://openalex.org/I165779595"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011808178","display_name":"Ni Ding","orcid":"https://orcid.org/0000-0003-1705-7380"},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Ni Ding","raw_affiliation_strings":["The University of Melbourne,School of Computing and Information Systems,Parkville,Australia","School of Computing and Information Systems, The University of Melbourne, Parkville, Australia"],"affiliations":[{"raw_affiliation_string":"The University of Melbourne,School of Computing and Information Systems,Parkville,Australia","institution_ids":["https://openalex.org/I165779595"]},{"raw_affiliation_string":"School of Computing and Information Systems, The University of Melbourne, Parkville, Australia","institution_ids":["https://openalex.org/I165779595"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5068636477"],"corresponding_institution_ids":["https://openalex.org/I165779595"],"apc_list":null,"apc_paid":null,"fwci":0.9518,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.79894145,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9984999895095825,"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":0.9984999895095825,"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":0.9966999888420105,"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":0.9923999905586243,"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/information-leakage","display_name":"Information leakage","score":0.7858049869537354},{"id":"https://openalex.org/keywords/adversary","display_name":"Adversary","score":0.7762004733085632},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5843647718429565},{"id":"https://openalex.org/keywords/minimax","display_name":"Minimax","score":0.5645958185195923},{"id":"https://openalex.org/keywords/private-information-retrieval","display_name":"Private information retrieval","score":0.5574726462364197},{"id":"https://openalex.org/keywords/brute-force","display_name":"Brute force","score":0.5529895424842834},{"id":"https://openalex.org/keywords/leakage","display_name":"Leakage (economics)","score":0.5422026515007019},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5231548547744751},{"id":"https://openalex.org/keywords/mutual-information","display_name":"Mutual information","score":0.47213345766067505},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.43475937843322754},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.38742595911026},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.3602791130542755},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3160253167152405},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.22925016283988953},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.20696166157722473},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.20155391097068787}],"concepts":[{"id":"https://openalex.org/C2779201187","wikidata":"https://www.wikidata.org/wiki/Q2775060","display_name":"Information leakage","level":2,"score":0.7858049869537354},{"id":"https://openalex.org/C41065033","wikidata":"https://www.wikidata.org/wiki/Q2825412","display_name":"Adversary","level":2,"score":0.7762004733085632},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5843647718429565},{"id":"https://openalex.org/C149728462","wikidata":"https://www.wikidata.org/wiki/Q751319","display_name":"Minimax","level":2,"score":0.5645958185195923},{"id":"https://openalex.org/C99221444","wikidata":"https://www.wikidata.org/wiki/Q1532069","display_name":"Private information retrieval","level":2,"score":0.5574726462364197},{"id":"https://openalex.org/C2986801135","wikidata":"https://www.wikidata.org/wiki/Q1209494","display_name":"Brute force","level":2,"score":0.5529895424842834},{"id":"https://openalex.org/C2777042071","wikidata":"https://www.wikidata.org/wiki/Q6509304","display_name":"Leakage (economics)","level":2,"score":0.5422026515007019},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5231548547744751},{"id":"https://openalex.org/C152139883","wikidata":"https://www.wikidata.org/wiki/Q252973","display_name":"Mutual information","level":2,"score":0.47213345766067505},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.43475937843322754},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.38742595911026},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.3602791130542755},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3160253167152405},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.22925016283988953},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.20696166157722473},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.20155391097068787},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C139719470","wikidata":"https://www.wikidata.org/wiki/Q39680","display_name":"Macroeconomics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/itw46852.2021.9457602","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itw46852.2021.9457602","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Information Theory Workshop (ITW)","raw_type":"proceedings-article"},{"id":"pmh:oai:jupiter.its.unimelb.edu.au:11343/278811","is_oa":true,"landing_page_url":"http://hdl.handle.net/11343/278811","pdf_url":"http://hdl.handle.net/11343/278811","source":{"id":"https://openalex.org/S4377196259","display_name":"Minerva Access (University of Melbourne)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I165779595","host_organization_name":"The University of Melbourne","host_organization_lineage":["https://openalex.org/I165779595"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2020 IEEE Information Theory Workshop (ITW)","raw_type":"Conference Paper"},{"id":"pmh:oai:jupiter.its.unimelb.edu.au:11343/285053","is_oa":false,"landing_page_url":"http://hdl.handle.net/11343/285053","pdf_url":null,"source":{"id":"https://openalex.org/S4377196259","display_name":"Minerva Access (University of Melbourne)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I165779595","host_organization_name":"The University of Melbourne","host_organization_lineage":["https://openalex.org/I165779595"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2020 IEEE Information Theory Workshop (ITW)","raw_type":"Conference Paper"}],"best_oa_location":{"id":"pmh:oai:jupiter.its.unimelb.edu.au:11343/278811","is_oa":true,"landing_page_url":"http://hdl.handle.net/11343/278811","pdf_url":"http://hdl.handle.net/11343/278811","source":{"id":"https://openalex.org/S4377196259","display_name":"Minerva Access (University of Melbourne)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I165779595","host_organization_name":"The University of Melbourne","host_organization_lineage":["https://openalex.org/I165779595"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2020 IEEE Information Theory Workshop (ITW)","raw_type":"Conference Paper"},"sustainable_development_goals":[{"score":0.699999988079071,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3173424199.pdf","grobid_xml":"https://content.openalex.org/works/W3173424199.grobid-xml"},"referenced_works_count":26,"referenced_works":["https://openalex.org/W1497454515","https://openalex.org/W1545744341","https://openalex.org/W1873763122","https://openalex.org/W1899372466","https://openalex.org/W2005201105","https://openalex.org/W2056963858","https://openalex.org/W2104866660","https://openalex.org/W2122882636","https://openalex.org/W2123097583","https://openalex.org/W2294409705","https://openalex.org/W2540895903","https://openalex.org/W2564029303","https://openalex.org/W2783589032","https://openalex.org/W2805329953","https://openalex.org/W2898223812","https://openalex.org/W2962719046","https://openalex.org/W2975348602","https://openalex.org/W2998261580","https://openalex.org/W3020222398","https://openalex.org/W3036459979","https://openalex.org/W3098386673","https://openalex.org/W3173424199","https://openalex.org/W4252822198","https://openalex.org/W6629769705","https://openalex.org/W6639246211","https://openalex.org/W6776557695"],"related_works":["https://openalex.org/W2122029840","https://openalex.org/W3080908196","https://openalex.org/W2784486299","https://openalex.org/W3122800147","https://openalex.org/W3128892202","https://openalex.org/W3002570285","https://openalex.org/W4226134241","https://openalex.org/W4289655080","https://openalex.org/W4287102274","https://openalex.org/W4312206423"],"abstract_inverted_index":{"We":[0,20,48,122],"propose":[1],"an":[2,36,55],"operational":[3],"measure":[4,117,129],"of":[5,26,63,82,86,94,101,118,130],"information":[6,43,66,120,131,135],"leakage":[7,132,139],"in":[8,34,40,53,91,98,106,145],"a":[9,16,31,116],"non-stochastic":[10],"setting":[11],"to":[12,29,74,143],"formalize":[13],"privacy":[14],"against":[15],"brute-force":[17,50],"guessing":[18,32,52,109],"adversary.":[19],"use":[21],"uncertain":[22,46],"variables,":[23,28],"non-probabilistic":[24],"counterparts":[25],"random":[27],"construct":[30],"framework":[33],"which":[35,54],"adversary":[37,56,90],"is":[38,112],"interested":[39],"determining":[41],"private":[42,65,78,119],"based":[44],"on":[45],"reports.":[47],"consider":[49],"trial-and-error":[51],"can":[57],"potentially":[58],"check":[59],"all":[60],"the":[61,64,71,76,83,89,92,95,99,104,107,124,127],"possibilities":[62],"that":[67,140],"are":[68,141],"compatible":[69],"with":[70,133],"available":[72],"outputs":[73],"find":[75],"actual":[77],"realization.":[79],"The":[80],"ratio":[81],"worst-case":[84],"number":[85],"guesses":[87],"for":[88],"presence":[93],"output":[96],"and":[97,111,136],"absence":[100],"it":[102],"captures":[103],"reduction":[105],"adversary\u2019s":[108],"complexity":[110],"thus":[113],"used":[114],"as":[115],"leakage.":[121],"investigate":[123],"relationship":[125],"between":[126],"newly-developed":[128],"maximin":[134],"stochastic":[137],"maximal":[138],"shown":[142],"arise":[144],"one-shot":[146],"guessing.":[147]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-18T23:42:31.664661","created_date":"2025-10-10T00:00:00"}