{"id":"https://openalex.org/W4386576644","doi":"https://doi.org/10.18653/v1/2023.findings-eacl.1","title":"Using Punctuation as an Adversarial Attack on Deep Learning-Based NLP Systems: An Empirical Study","display_name":"Using Punctuation as an Adversarial Attack on Deep Learning-Based NLP Systems: An Empirical Study","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4386576644","doi":"https://doi.org/10.18653/v1/2023.findings-eacl.1"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2023.findings-eacl.1","doi":"https://doi.org/10.18653/v1/2023.findings-eacl.1","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2023.findings-eacl.1","pdf_url":"https://aclanthology.org/2023.findings-eacl.1.pdf","source":{"id":"https://openalex.org/S7407087051","display_name":"Findings of the Association for Computational Linguistics: EACL","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: EACL 2023","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://aclanthology.org/2023.findings-eacl.1.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5001319605","display_name":"Brian Formento","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]},{"id":"https://openalex.org/I3005327000","display_name":"Institute for Infocomm Research","ror":"https://ror.org/053rfa017","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I3005327000","https://openalex.org/I91275662"]},{"id":"https://openalex.org/I4405278236","display_name":"Institute of Data Science","ror":"https://ror.org/05e141s81","country_code":"SG","type":"facility","lineage":["https://openalex.org/I4405278236"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Brian Formento","raw_affiliation_strings":["Institute for Infocomm Research, A","Institute of Data Science, National University of Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Infocomm Research, A","institution_ids":["https://openalex.org/I3005327000"]},{"raw_affiliation_string":"Institute of Data Science, National University of Singapore","institution_ids":["https://openalex.org/I165932596","https://openalex.org/I4405278236"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001103949","display_name":"Chuan-Sheng Foo","orcid":"https://orcid.org/0000-0002-4748-5792","observed_orcids":["https://orcid.org/0000-0002-4748-5792"]},"institutions":[{"id":"https://openalex.org/I3005327000","display_name":"Institute for Infocomm Research","ror":"https://ror.org/053rfa017","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I3005327000","https://openalex.org/I91275662"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Chuan Sheng Foo","raw_affiliation_strings":["Centre for Frontier AI Research, A","Institute for Infocomm Research, A"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Centre for Frontier AI Research, A","institution_ids":[]},{"raw_affiliation_string":"Institute for Infocomm Research, A","institution_ids":["https://openalex.org/I3005327000"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001659855","display_name":"Luu Anh Tuan","orcid":"https://orcid.org/0000-0001-6062-207X","observed_orcids":["https://orcid.org/0000-0001-6062-207X","https://orcid.org/0000-0002-6477-1766"]},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Luu Anh Tuan","raw_affiliation_strings":["Nanyang Technological University","STAR"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanyang Technological University","institution_ids":["https://openalex.org/I172675005"]},{"raw_affiliation_string":"STAR","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110918847","display_name":"See Kiong Ng","orcid":"https://orcid.org/0000-0001-6565-7511","observed_orcids":["https://orcid.org/0000-0001-6565-7511"]},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]},{"id":"https://openalex.org/I4405278236","display_name":"Institute of Data Science","ror":"https://ror.org/05e141s81","country_code":"SG","type":"facility","lineage":["https://openalex.org/I4405278236"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"See Kiong Ng","raw_affiliation_strings":["Institute of Data Science, National University of Singapore","STAR"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Data Science, National University of Singapore","institution_ids":["https://openalex.org/I165932596","https://openalex.org/I4405278236"]},{"raw_affiliation_string":"STAR","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5001319605"],"corresponding_institution_ids":["https://openalex.org/I165932596","https://openalex.org/I3005327000","https://openalex.org/I4405278236"],"apc_list":null,"apc_paid":null,"fwci":2.3199,"has_fulltext":true,"cited_by_count":21,"citation_normalized_percentile":{"value":0.91923708,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"34"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":1.0,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":1.0,"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":0.0,"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":0.0,"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/adversarial-attacks","display_name":"adversarial attacks","score":0.9660000205039978},{"id":"https://openalex.org/keywords/adversarial-robustness","display_name":"adversarial robustness","score":0.6850000023841858},{"id":"https://openalex.org/keywords/semantic-similarity","display_name":"semantic similarity","score":0.6119999885559082},{"id":"https://openalex.org/keywords/readability","display_name":"readability","score":0.7369999885559082},{"id":"https://openalex.org/keywords/grammar-checking","display_name":"grammar checking","score":0.7570000290870667},{"id":"https://openalex.org/keywords/attack-mitigation","display_name":"attack mitigation","score":0.6869999766349792}],"concepts":[{"id":"https://openalex.org/C540372491","wikidata":"https://www.wikidata.org/wiki/Q82622","display_name":"Punctuation","level":2,"score":0.9577618837356567},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8169215321540833},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6597762107849121},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6020846366882324},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.5438232421875},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.45845121145248413},{"id":"https://openalex.org/C26022165","wikidata":"https://www.wikidata.org/wiki/Q8091","display_name":"Grammar","level":2,"score":0.4369361996650696},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3270939588546753},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.17647016048431396},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2023.findings-eacl.1","doi":"https://doi.org/10.18653/v1/2023.findings-eacl.1","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2023.findings-eacl.1","pdf_url":"https://aclanthology.org/2023.findings-eacl.1.pdf","source":{"id":"https://openalex.org/S7407087051","display_name":"Findings of the Association for Computational Linguistics: EACL","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: EACL 2023","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2023.findings-eacl.1","doi":"https://doi.org/10.18653/v1/2023.findings-eacl.1","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2023.findings-eacl.1","pdf_url":"https://aclanthology.org/2023.findings-eacl.1.pdf","source":{"id":"https://openalex.org/S7407087051","display_name":"Findings of the Association for Computational Linguistics: EACL","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: EACL 2023","raw_type":"proceedings-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4386576644.pdf","grobid_xml":"https://content.openalex.org/works/W4386576644.grobid-xml"},"referenced_works_count":13,"referenced_works":["https://openalex.org/W2039117335","https://openalex.org/W2594590228","https://openalex.org/W2767899794","https://openalex.org/W2799194071","https://openalex.org/W2891177506","https://openalex.org/W2962782614","https://openalex.org/W2962818281","https://openalex.org/W2963341956","https://openalex.org/W2963823140","https://openalex.org/W2996851481","https://openalex.org/W3092347010","https://openalex.org/W3176393001","https://openalex.org/W3201816072"],"related_works":["https://openalex.org/W7111775999","https://openalex.org/W4407269018","https://openalex.org/W4387427990","https://openalex.org/W3176393001","https://openalex.org/W7133225584","https://openalex.org/W7034107437","https://openalex.org/W3049509967","https://openalex.org/W3105604018","https://openalex.org/W7091510640","https://openalex.org/W4283789713"],"abstract_inverted_index":{"This":[0],"work":[1],"empirically":[2],"investigates":[3],"punctuation":[4,27,104,108,134,155,162],"insertions":[5,46,105,109],"as":[6,84],"adversarial":[7],"attacks":[8,24,112],"on":[9,14],"NLP":[10],"systems.Data":[11],"from":[12],"experiments":[13],"three":[15],"tasks,":[16],"five":[17],"datasets,":[18],"and":[19,36,69,72,80,106,122,166],"six":[20],"models":[21],"with":[22,86,115],"four":[23],"show":[25],"that":[26,77,97,130,136,176],"insertions,":[28,156],"when":[29],"limited":[30,117],"to":[31,44,48,82,124],"a":[32,39,50,74,116,132,142,171],"few":[33,133],"symbols":[34],"(apostrophes":[35],"hyphens),":[37],"are":[38],"superior":[40],"attack":[41,144],"vector":[42],"compared":[43],"character":[45,60],"due":[47],"1)":[49],"lower":[51],"after-attack":[52],"accuracy":[53],"(A":[54],"af":[55],"t-atk":[56],")":[57],"than":[58],"alphabetical":[59],"insertions;":[61],"2)":[62],"higher":[63],"semantic":[64],"similarity":[65],"between":[66],"the":[67,87,125,152,159],"resulting":[68,75],"original":[70],"texts;":[71],"3)":[73],"text":[76],"is":[78,141],"easier":[79],"faster":[81],"read":[83],"assessed":[85],"Test":[88],"of":[89,119,147,154],"Word":[90],"Reading":[91],"Efficiency":[92],"(TOWRE)).The":[93],"tests":[94],"also":[95],"indicate":[96,129],"4)":[98],"grammar":[99],"checking":[100],"does":[101],"not":[102],"mitigate":[103],"5)":[107],"outperform":[110],"word-level":[111],"in":[113,138,170],"settings":[114],"number":[118],"word":[120],"synonyms":[121],"queries":[123],"victim's":[126],"model.Our":[127],"findings":[128,169],"inserting":[131],"types":[135],"result":[137],"easy-to-read":[139],"samples":[140],"general":[143],"mechanism.In":[145],"light":[146],"this":[148],"threat,":[149],"we":[150],"assess":[151],"impact":[153],"potential":[157],"mitigations,":[158],"mitigation's":[160],"tradeoffs,":[161],"insertion's":[163],"worst-case":[164],"scenarios":[165],"summarize":[167],"our":[168],"qualitative":[172],"casual":[173],"map,":[174],"so":[175],"developers":[177],"can":[178],"design":[179],"safer,":[180],"more":[181],"secure":[182],"systems.":[183]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":14}],"updated_date":"2026-11-10T11:39:43.021295","created_date":"2023-09-10T00:00:00"}