{"id":"https://openalex.org/W2912558641","doi":"https://doi.org/10.1109/ssci.2018.8628894","title":"The Impact of an Adversary in a Language Model","display_name":"The Impact of an Adversary in a Language Model","publication_year":2018,"publication_date":"2018-11-01","ids":{"openalex":"https://openalex.org/W2912558641","doi":"https://doi.org/10.1109/ssci.2018.8628894","mag":"2912558641"},"language":"en","primary_location":{"id":"doi:10.1109/ssci.2018.8628894","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssci.2018.8628894","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE Symposium Series on Computational Intelligence (SSCI)","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/A5067020441","display_name":"Zhengzhong Liang","orcid":"https://orcid.org/0000-0003-0705-4880"},"institutions":[{"id":"https://openalex.org/I138006243","display_name":"University of Arizona","ror":"https://ror.org/03m2x1q45","country_code":"US","type":"education","lineage":["https://openalex.org/I138006243"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Zhengzhong Liang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Arizona, Tucson, AZ, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Arizona, Tucson, AZ, USA","institution_ids":["https://openalex.org/I138006243"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079638101","display_name":"Gregory Ditzler","orcid":"https://orcid.org/0000-0001-6890-0935"},"institutions":[{"id":"https://openalex.org/I138006243","display_name":"University of Arizona","ror":"https://ror.org/03m2x1q45","country_code":"US","type":"education","lineage":["https://openalex.org/I138006243"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gregory Ditzler","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Arizona, Tucson, AZ, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Arizona, Tucson, AZ, USA","institution_ids":["https://openalex.org/I138006243"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5067020441"],"corresponding_institution_ids":["https://openalex.org/I138006243"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1743587,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"3","issue":null,"first_page":"658","last_page":"665"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9980000257492065,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9944000244140625,"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/adversary","display_name":"Adversary","score":0.8952425718307495},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.8664594888687134},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8422907590866089},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.7113828659057617},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6489620804786682},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.6031347513198853},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5329991579055786},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.49145376682281494},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.46855291724205017},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4609568417072296},{"id":"https://openalex.org/keywords/volume","display_name":"Volume (thermodynamics)","score":0.45276394486427307},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.4338172674179077},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.3727567195892334}],"concepts":[{"id":"https://openalex.org/C41065033","wikidata":"https://www.wikidata.org/wiki/Q2825412","display_name":"Adversary","level":2,"score":0.8952425718307495},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.8664594888687134},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8422907590866089},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.7113828659057617},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6489620804786682},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.6031347513198853},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5329991579055786},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.49145376682281494},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.46855291724205017},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4609568417072296},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.45276394486427307},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.4338172674179077},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.3727567195892334},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ssci.2018.8628894","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssci.2018.8628894","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE Symposium Series on Computational Intelligence (SSCI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W182831726","https://openalex.org/W1591801644","https://openalex.org/W1673923490","https://openalex.org/W1682403713","https://openalex.org/W1945616565","https://openalex.org/W1968411139","https://openalex.org/W2042281163","https://openalex.org/W2083780116","https://openalex.org/W2085302848","https://openalex.org/W2095577883","https://openalex.org/W2112507308","https://openalex.org/W2143612262","https://openalex.org/W2163605009","https://openalex.org/W2167421362","https://openalex.org/W2560647685","https://openalex.org/W2562979205","https://openalex.org/W2591602089","https://openalex.org/W2620038827","https://openalex.org/W2760600531","https://openalex.org/W2766108848","https://openalex.org/W2949506549","https://openalex.org/W2963207607","https://openalex.org/W2963389226","https://openalex.org/W2963744840","https://openalex.org/W2963888996","https://openalex.org/W2963969878","https://openalex.org/W2964043980","https://openalex.org/W2964153729","https://openalex.org/W6635446068","https://openalex.org/W6637162671","https://openalex.org/W6640425456","https://openalex.org/W6676935882","https://openalex.org/W6684191040","https://openalex.org/W6684559340","https://openalex.org/W6729756640","https://openalex.org/W6730559633","https://openalex.org/W6734354522","https://openalex.org/W6739088070","https://openalex.org/W6745847742"],"related_works":["https://openalex.org/W4320018150","https://openalex.org/W2040808657","https://openalex.org/W2918664383","https://openalex.org/W4320855730","https://openalex.org/W106056076","https://openalex.org/W2135200719","https://openalex.org/W2950183588","https://openalex.org/W3080754722","https://openalex.org/W4383221314","https://openalex.org/W3093978547"],"abstract_inverted_index":{"Neural":[0],"networks":[1,111],"have":[2,12,59],"been":[3],"quite":[4],"successful":[5],"at":[6],"complex":[7],"classification":[8],"tasks.":[9],"Furthermore,":[10,152],"they":[11],"the":[13,28,42,45,55,77,88,98,118,163,171],"ability":[14],"to":[15,48,53,58,68,76,145,159,169],"learn":[16],"information":[17],"from":[18,130,153],"a":[19,36,50,60,72,133],"large":[20],"volume":[21],"of":[22,27,90,100,173],"data.":[23,92],"Unfortunately,":[24],"not":[25],"all":[26],"sources":[29],"available":[30],"are":[31,141,157],"secure":[32],"and":[33,87,112,124],"there":[34,140],"is":[35,66,75],"possibility":[37],"that":[38,127,139,165],"an":[39,101,148],"adversary":[40,102],"in":[41,132],"environment":[43],"has":[44],"malicious":[46],"intention":[47],"poison":[49,146],"training":[51],"dataset":[52,123],"cause":[54],"neural":[56,73],"network":[57,74],"poor":[61],"generalization":[62],"error.":[63],"Therefore,":[64],"it":[65],"important":[67],"observe":[69],"how":[70],"susceptible":[71],"free":[78],"parameters":[79],"(i.e.,":[80],"gradient":[81],"thresholds,":[82],"hidden":[83],"layer":[84],"size,":[85],"etc.)":[86],"availability":[89],"adversarial":[91,125],"In":[93],"this":[94],"work,":[95],"we":[96,156],"study":[97],"impact":[99,172],"for":[103],"language":[104,150],"models":[105],"with":[106,117],"Long":[107],"Short-Term":[108],"Memory":[109],"(LSTM)":[110],"its":[113],"configurations.":[114],"We":[115],"experimented":[116],"Penn":[119],"Tree":[120],"Bank":[121],"(PTB)":[122],"text":[126],"was":[128],"sampled":[129],"works":[131],"different":[134],"era.":[135],"Our":[136],"results":[137],"show":[138],"several":[142],"effective":[143],"ways":[144],"such":[147,174],"LSTM":[149],"model.":[151],"our":[154],"experiments,":[155],"able":[158],"provide":[160],"suggestions":[161],"about":[162],"steps":[164],"can":[166],"be":[167],"taken":[168],"reduce":[170],"attacks.":[175]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
