{"id":"https://openalex.org/W7091510640","doi":"https://doi.org/10.1109/tifs.2025.3622073","title":"AdvChar: Attacking Interpretable NLP Systems","display_name":"AdvChar: Attacking Interpretable NLP Systems","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W7091510640","doi":"https://doi.org/10.1109/tifs.2025.3622073"},"language":"en","primary_location":{"id":"doi:10.1109/tifs.2025.3622073","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2025.3622073","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":true,"oa_status":"green","oa_url":"https://ecommons.luc.edu/cs_facpubs/442","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Eldor Abdukhamidov","orcid":"https://orcid.org/0000-0001-8530-9477"},"institutions":[{"id":"https://openalex.org/I848706","display_name":"Sungkyunkwan University","ror":"https://ror.org/04q78tk20","country_code":"KR","type":"education","lineage":["https://openalex.org/I848706"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Eldor Abdukhamidov","raw_affiliation_strings":["Department of Computer Science and Engineering, Sungkyunkwan University, Suwon, South Korea"],"raw_orcid":"https://orcid.org/0000-0001-8530-9477","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Sungkyunkwan University, Suwon, South Korea","institution_ids":["https://openalex.org/I848706"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Tamer Abuhmed","orcid":"https://orcid.org/0000-0001-9232-4843"},"institutions":[{"id":"https://openalex.org/I848706","display_name":"Sungkyunkwan University","ror":"https://ror.org/04q78tk20","country_code":"KR","type":"education","lineage":["https://openalex.org/I848706"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Tamer Abuhmed","raw_affiliation_strings":["Department of Computer Science and Engineering, Sungkyunkwan University, Suwon, South Korea"],"raw_orcid":"https://orcid.org/0000-0001-9232-4843","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Sungkyunkwan University, Suwon, South Korea","institution_ids":["https://openalex.org/I848706"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Joanna C. S. Santos","orcid":"https://orcid.org/0000-0001-8743-2516"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Joanna C. S. Santos","raw_affiliation_strings":["Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA"],"raw_orcid":"https://orcid.org/0000-0001-8743-2516","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"last","author":{"id":null,"display_name":"Mohammed Abuhamad","orcid":"https://orcid.org/0000-0002-3368-6024"},"institutions":[{"id":"https://openalex.org/I1925986","display_name":"Loyola University Chicago","ror":"https://ror.org/04b6x2g63","country_code":"US","type":"education","lineage":["https://openalex.org/I1925986"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mohammed Abuhamad","raw_affiliation_strings":["Department of Computer Science, Loyola University Chicago, Chicago, IL, USA"],"raw_orcid":"https://orcid.org/0000-0002-3368-6024","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Loyola University Chicago, Chicago, IL, USA","institution_ids":["https://openalex.org/I1925986"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.69756929,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"20","issue":null,"first_page":"11342","last_page":"11354"},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9107000231742859,"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":0.9107000231742859,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.05920000001788139,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.004900000058114529,"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/classifier","display_name":"Classifier (UML)","score":0.7347999811172485},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.6550999879837036},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.6157000064849854},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.42289999127388},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.40849998593330383},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.3871999979019165},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.3368000090122223}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8519999980926514},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.767300009727478},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.7347999811172485},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.6550999879837036},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.6157000064849854},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5882999897003174},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5724999904632568},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.42289999127388},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.40849998593330383},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.3871999979019165},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.3368000090122223},{"id":"https://openalex.org/C2779439875","wikidata":"https://www.wikidata.org/wiki/Q1078276","display_name":"Natural language understanding","level":3,"score":0.3361999988555908},{"id":"https://openalex.org/C193125573","wikidata":"https://www.wikidata.org/wiki/Q7449065","display_name":"Semantic interpretation","level":2,"score":0.33169999718666077},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.32510000467300415},{"id":"https://openalex.org/C139532973","wikidata":"https://www.wikidata.org/wiki/Q2679259","display_name":"Linear classifier","level":3,"score":0.3052999973297119},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.29510000348091125},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.289000004529953},{"id":"https://openalex.org/C527412718","wikidata":"https://www.wikidata.org/wiki/Q855395","display_name":"Interpretation (philosophy)","level":2,"score":0.28839999437332153},{"id":"https://openalex.org/C197115733","wikidata":"https://www.wikidata.org/wiki/Q1003136","display_name":"Forcing (mathematics)","level":2,"score":0.26440000534057617}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tifs.2025.3622073","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2025.3622073","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"},{"id":"pmh:oai:ecommons.luc.edu:cs_facpubs-1435","is_oa":true,"landing_page_url":"https://ecommons.luc.edu/cs_facpubs/442","pdf_url":null,"source":{"id":"https://openalex.org/S4377196418","display_name":"Loyola eCommons (Loyola University Chicago)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1925986","host_organization_name":"Loyola University Chicago","host_organization_lineage":["https://openalex.org/I1925986"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Computer Science: Faculty Publications and Other Works","raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:ecommons.luc.edu:cs_facpubs-1435","is_oa":true,"landing_page_url":"https://ecommons.luc.edu/cs_facpubs/442","pdf_url":null,"source":{"id":"https://openalex.org/S4377196418","display_name":"Loyola eCommons (Loyola University Chicago)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1925986","host_organization_name":"Loyola University Chicago","host_organization_lineage":["https://openalex.org/I1925986"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Computer Science: Faculty Publications and Other Works","raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1128486320","display_name":null,"funder_award_id":"2021R1A2C1011198","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G1208298189","display_name":null,"funder_award_id":"IITP-2021-2020-0-01821","funder_id":"https://openalex.org/F4320335489","funder_display_name":"Institute for Information and Communications Technology Promotion"}],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"},{"id":"https://openalex.org/F4320335489","display_name":"Institute for Information and Communications Technology Promotion","ror":"https://ror.org/01g0hqq23"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W2251939518","https://openalex.org/W2516809705","https://openalex.org/W2905526464","https://openalex.org/W2947415936","https://openalex.org/W2949128310","https://openalex.org/W2962858109","https://openalex.org/W2996851481","https://openalex.org/W3015001695","https://openalex.org/W3027026357","https://openalex.org/W3035390927","https://openalex.org/W3037045905","https://openalex.org/W3090350559","https://openalex.org/W3135427360","https://openalex.org/W3161207330","https://openalex.org/W3162090017","https://openalex.org/W3162748751","https://openalex.org/W3174848559","https://openalex.org/W3206421646","https://openalex.org/W4205690221","https://openalex.org/W4225858632","https://openalex.org/W4281399026","https://openalex.org/W4308487733","https://openalex.org/W4312398513","https://openalex.org/W4379051468","https://openalex.org/W4389584466","https://openalex.org/W4390490761","https://openalex.org/W4390590855","https://openalex.org/W4390604007","https://openalex.org/W4392168447","https://openalex.org/W4393156804","https://openalex.org/W4399169124","https://openalex.org/W4399835044","https://openalex.org/W4409095687"],"related_works":[],"abstract_inverted_index":{"Studies":[0],"have":[1,19,36],"shown":[2],"that":[3,25,191],"machine":[4,32],"learning":[5,104,202],"systems":[6],"are":[7],"vulnerable":[8],"to":[9,40,48,72,81,98,106,121,134,143,163],"adversarial":[10,160],"examples":[11],"in":[12,87,211],"theory":[13],"and":[14,31,56,110,155,177],"practice.":[15],"Where":[16],"previous":[17],"attacks":[18,45],"focused":[20],"mainly":[21],"on":[22,65,209],"visual":[23],"models":[24,35,176,180,203],"exploit":[26],"the":[27,50,54,74,78,102,112,123,132,136,145,150,153,185,196],"difference":[28,151],"between":[29,152],"human":[30],"perception,":[33],"text-based":[34],"also":[37],"fallen":[38],"victim":[39],"these":[41,44],"attacks.":[42],"However,":[43],"often":[46],"fail":[47],"maintain":[49],"semantic":[51],"meaning":[52],"of":[53,147,199],"text":[55,99,157],"similarity.":[57],"This":[58],"paper":[59],"introduces":[60],"AdvChar,":[61],"a":[62],"black-box":[63],"attack":[64],"Interpretable":[66],"Natural":[67],"Language":[68],"Processing":[69],"Systems,":[70],"designed":[71],"mislead":[73],"classifier":[75,105,133],"while":[76,158],"keeping":[77],"interpretation":[79,179],"similar":[80,162],"benign":[82,164],"inputs,":[83],"thus":[84],"exploiting":[85],"trust":[86],"system":[88],"transparency.":[89],"AdvChar":[90,169,192],"achieves":[91],"this":[92],"by":[93,170,204],"making":[94],"less":[95],"noticeable":[96],"modifications":[97,142],"input,":[100],"forcing":[101],"deep":[103,201],"make":[107],"incorrect":[108],"predictions":[109],"preserve":[111],"original":[113,154],"interpretation.":[114],"We":[115,138,166],"use":[116],"an":[117],"interpretation-focused":[118],"scoring":[119],"approach":[120],"determine":[122],"most":[124],"critical":[125],"tokens":[126],"that,":[127],"when":[128],"changed,":[129],"can":[130,193],"cause":[131],"misclassify":[135],"input.":[137],"apply":[139],"simple":[140],"character-level":[141],"measure":[144],"importance":[146],"tokens,":[148],"minimizing":[149],"new":[156],"generating":[159],"interpretations":[161],"ones.":[165],"thoroughly":[167],"evaluated":[168],"testing":[171],"it":[172],"against":[173],"seven":[174],"NLP":[175],"three":[178],"using":[181],"benchmark":[182],"datasets":[183],"for":[184],"classification":[186],"task.":[187],"Our":[188],"experiments":[189],"show":[190],"significantly":[194],"reduce":[195],"prediction":[197],"accuracy":[198],"current":[200],"altering":[205],"just":[206],"two":[207],"characters":[208],"average":[210],"input":[212],"samples.":[213]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-16T00:00:00"}
