{"id":"https://openalex.org/W4308411238","doi":"https://doi.org/10.1145/3548606.3563512","title":"Poster Towards Authorship Obfuscation with Language Models","display_name":"Poster Towards Authorship Obfuscation with Language Models","publication_year":2022,"publication_date":"2022-11-07","ids":{"openalex":"https://openalex.org/W4308411238","doi":"https://doi.org/10.1145/3548606.3563512"},"language":"en","primary_location":{"id":"doi:10.1145/3548606.3563512","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3548606.3563512","pdf_url":null,"source":{"id":"https://openalex.org/S4363608815","display_name":"Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security","issn_l":null,"issn":null,"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security","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/A5001097796","display_name":"Rajvardhan Oak","orcid":"https://orcid.org/0000-0003-1928-099X"},"institutions":[{"id":"https://openalex.org/I84218800","display_name":"University of California, Davis","ror":"https://ror.org/05rrcem69","country_code":"US","type":"education","lineage":["https://openalex.org/I84218800"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Rajvardhan Oak","raw_affiliation_strings":["University of California, Davis, Davis, CA, USA"],"affiliations":[{"raw_affiliation_string":"University of California, Davis, Davis, CA, USA","institution_ids":["https://openalex.org/I84218800"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5001097796"],"corresponding_institution_ids":["https://openalex.org/I84218800"],"apc_list":null,"apc_paid":null,"fwci":0.2078,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.42334626,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"3435","last_page":"3437"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12380","display_name":"Authorship Attribution and Profiling","score":0.9998999834060669,"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/T12380","display_name":"Authorship Attribution and Profiling","score":0.9998999834060669,"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/T10028","display_name":"Topic Modeling","score":0.9980999827384949,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9933000206947327,"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/obfuscation","display_name":"Obfuscation","score":0.8958600759506226},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8375203609466553},{"id":"https://openalex.org/keywords/automatic-summarization","display_name":"Automatic summarization","score":0.7729368209838867},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6786737442016602},{"id":"https://openalex.org/keywords/meaning","display_name":"Meaning (existential)","score":0.5517187714576721},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5338716506958008},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5190659165382385},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49343815445899963},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.48066699504852295},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.43397021293640137},{"id":"https://openalex.org/keywords/tone","display_name":"Tone (literature)","score":0.4316735565662384},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.30258363485336304},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.14674538373947144},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.08022841811180115}],"concepts":[{"id":"https://openalex.org/C40305131","wikidata":"https://www.wikidata.org/wiki/Q2616305","display_name":"Obfuscation","level":2,"score":0.8958600759506226},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8375203609466553},{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.7729368209838867},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6786737442016602},{"id":"https://openalex.org/C2780876879","wikidata":"https://www.wikidata.org/wiki/Q3054749","display_name":"Meaning (existential)","level":2,"score":0.5517187714576721},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5338716506958008},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5190659165382385},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49343815445899963},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.48066699504852295},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.43397021293640137},{"id":"https://openalex.org/C2780583480","wikidata":"https://www.wikidata.org/wiki/Q1366327","display_name":"Tone (literature)","level":2,"score":0.4316735565662384},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.30258363485336304},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.14674538373947144},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.08022841811180115},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C542102704","wikidata":"https://www.wikidata.org/wiki/Q183257","display_name":"Psychotherapist","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3548606.3563512","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3548606.3563512","pdf_url":null,"source":{"id":"https://openalex.org/S4363608815","display_name":"Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security","issn_l":null,"issn":null,"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.6499999761581421}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":2,"referenced_works":["https://openalex.org/W2119804197","https://openalex.org/W2949387767"],"related_works":["https://openalex.org/W2366403280","https://openalex.org/W1495108544","https://openalex.org/W2091301346","https://openalex.org/W3148229873","https://openalex.org/W4389760904","https://openalex.org/W2150160875","https://openalex.org/W4242223894","https://openalex.org/W4306886878","https://openalex.org/W1517524280","https://openalex.org/W4323520239"],"abstract_inverted_index":{"Authorship":[0],"obfuscation":[1,25,87],"is":[2,26,125],"the":[3,29,32,35,45,55,67,79,99,118,127,150,160,169],"process":[4],"of":[5,24,31,57,69,81,94,117,157,168],"making":[6],"changes":[7],"to":[8,27,77,132],"text":[9,33,95,162],"such":[10,41],"that":[11,44,107,123],"identifying":[12,115],"attributes":[13],"(style,":[14],"common":[15],"words":[16],"and":[17,136,159],"phrases,":[18],"tone)":[19],"are":[20,91],"masked.":[21],"The":[22],"goal":[23],"retain":[28,98],"semantics":[30],"(i.e.,":[34],"meaning)":[36],"but":[37,96],"rewrite":[38],"it":[39],"in":[40,103],"a":[42,82,154],"way":[43],"author":[46],"cannot":[47],"be":[48,110],"identified.":[49],"In":[50],"this":[51,124,146],"work,":[52],"we":[53,65,75,105,129],"investigate":[54],"effectiveness":[56],"language":[58],"models":[59],"for":[60],"authorship":[61,86,134],"obfuscation.":[62],"More":[63],"specifically,":[64],"examine":[66],"application":[68],"document":[70],"summarization":[71],"(a":[72],"task":[73],"where":[74],"learn":[76],"generate":[78],"summary":[80],"text)":[83],"as":[84,141,143],"an":[85,165],"method.":[88],"Since":[89],"summaries":[90,108],"shorter":[92],"versions":[93],"which":[97],"significant":[100],"points":[101],"made":[102],"it,":[104],"hypothesize":[106],"will":[109],"stripped":[111],"off":[112],"any":[113],"stylistic":[114],"features":[116],"text.":[119],"Our":[120],"experiments":[121],"show":[122],"indeed":[126],"case;":[128],"were":[130],"able":[131],"fool":[133],"classifiers":[135],"degrade":[137],"their":[138],"performance":[139],"by":[140],"much":[142],"70%":[144],"However,":[145],"also":[147],"significantly":[148],"affected":[149],"semantics;":[151],"there":[152],"was":[153,163],"non-trivial":[155],"loss":[156],"information":[158],"produced":[161],"not":[164],"accurate":[166],"representation":[167],"original.":[170]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}