{"id":"https://openalex.org/W4293691716","doi":"https://doi.org/10.1109/hsi55341.2022.9869459","title":"Evaluating the Adversarial Robustness of Text Classifiers in Hyperdimensional Computing","display_name":"Evaluating the Adversarial Robustness of Text Classifiers in Hyperdimensional Computing","publication_year":2022,"publication_date":"2022-07-28","ids":{"openalex":"https://openalex.org/W4293691716","doi":"https://doi.org/10.1109/hsi55341.2022.9869459"},"language":"en","primary_location":{"id":"doi:10.1109/hsi55341.2022.9869459","is_oa":false,"landing_page_url":"https://doi.org/10.1109/hsi55341.2022.9869459","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 15th International Conference on Human System Interaction (HSI)","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/A5060827010","display_name":"Harsha Moraliyage","orcid":"https://orcid.org/0000-0002-6212-8312"},"institutions":[{"id":"https://openalex.org/I196829312","display_name":"La Trobe University","ror":"https://ror.org/01rxfrp27","country_code":"AU","type":"education","lineage":["https://openalex.org/I196829312"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Harsha Moraliyage","raw_affiliation_strings":["La Trobe University,Centre for Data Analytics and Cognition,Melbourne,Australia","Centre for Data Analytics and Cognition, La Trobe University, Melbourne, Australia"],"affiliations":[{"raw_affiliation_string":"La Trobe University,Centre for Data Analytics and Cognition,Melbourne,Australia","institution_ids":["https://openalex.org/I196829312"]},{"raw_affiliation_string":"Centre for Data Analytics and Cognition, La Trobe University, Melbourne, Australia","institution_ids":["https://openalex.org/I196829312"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071730776","display_name":"Sachin Kahawala","orcid":"https://orcid.org/0000-0003-0320-1337"},"institutions":[{"id":"https://openalex.org/I196829312","display_name":"La Trobe University","ror":"https://ror.org/01rxfrp27","country_code":"AU","type":"education","lineage":["https://openalex.org/I196829312"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Sachin Kahawala","raw_affiliation_strings":["La Trobe University,Centre for Data Analytics and Cognition,Melbourne,Australia","Centre for Data Analytics and Cognition, La Trobe University, Melbourne, Australia"],"affiliations":[{"raw_affiliation_string":"La Trobe University,Centre for Data Analytics and Cognition,Melbourne,Australia","institution_ids":["https://openalex.org/I196829312"]},{"raw_affiliation_string":"Centre for Data Analytics and Cognition, La Trobe University, Melbourne, Australia","institution_ids":["https://openalex.org/I196829312"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064845769","display_name":"Daswin De Silva","orcid":"https://orcid.org/0000-0003-3878-5969"},"institutions":[{"id":"https://openalex.org/I196829312","display_name":"La Trobe University","ror":"https://ror.org/01rxfrp27","country_code":"AU","type":"education","lineage":["https://openalex.org/I196829312"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Daswin De Silva","raw_affiliation_strings":["La Trobe University,Centre for Data Analytics and Cognition,Melbourne,Australia","Centre for Data Analytics and Cognition, La Trobe University, Melbourne, Australia"],"affiliations":[{"raw_affiliation_string":"La Trobe University,Centre for Data Analytics and Cognition,Melbourne,Australia","institution_ids":["https://openalex.org/I196829312"]},{"raw_affiliation_string":"Centre for Data Analytics and Cognition, La Trobe University, Melbourne, Australia","institution_ids":["https://openalex.org/I196829312"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008490552","display_name":"Damminda Alahakoon","orcid":"https://orcid.org/0000-0003-3291-888X"},"institutions":[{"id":"https://openalex.org/I196829312","display_name":"La Trobe University","ror":"https://ror.org/01rxfrp27","country_code":"AU","type":"education","lineage":["https://openalex.org/I196829312"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Damminda Alahakoon","raw_affiliation_strings":["La Trobe University,Centre for Data Analytics and Cognition,Melbourne,Australia","Centre for Data Analytics and Cognition, La Trobe University, Melbourne, Australia"],"affiliations":[{"raw_affiliation_string":"La Trobe University,Centre for Data Analytics and Cognition,Melbourne,Australia","institution_ids":["https://openalex.org/I196829312"]},{"raw_affiliation_string":"Centre for Data Analytics and Cognition, La Trobe University, Melbourne, Australia","institution_ids":["https://openalex.org/I196829312"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5060827010"],"corresponding_institution_ids":["https://openalex.org/I196829312"],"apc_list":null,"apc_paid":null,"fwci":0.6404,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.66338275,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9916999936103821,"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/computer-science","display_name":"Computer science","score":0.7669229507446289},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6906721591949463},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.6704221963882446},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6515330672264099},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5780988335609436},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5332040190696716},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44976741075515747}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7669229507446289},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6906721591949463},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.6704221963882446},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6515330672264099},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5780988335609436},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5332040190696716},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44976741075515747},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/hsi55341.2022.9869459","is_oa":false,"landing_page_url":"https://doi.org/10.1109/hsi55341.2022.9869459","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 15th International Conference on Human System Interaction (HSI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.7799999713897705,"display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W1673923490","https://openalex.org/W1832693441","https://openalex.org/W1945616565","https://openalex.org/W2070862086","https://openalex.org/W2170240176","https://openalex.org/W2243397390","https://openalex.org/W2250539671","https://openalex.org/W2476008461","https://openalex.org/W2528914598","https://openalex.org/W2759478409","https://openalex.org/W2771100829","https://openalex.org/W2799194071","https://openalex.org/W2895910969","https://openalex.org/W2897044384","https://openalex.org/W2905526464","https://openalex.org/W2943643445","https://openalex.org/W2947415936","https://openalex.org/W2949128310","https://openalex.org/W2962818281","https://openalex.org/W2963859254","https://openalex.org/W2963895533","https://openalex.org/W2972600208","https://openalex.org/W2996851481","https://openalex.org/W2998342322","https://openalex.org/W3004368638","https://openalex.org/W3032819016","https://openalex.org/W3037266788","https://openalex.org/W3084992427","https://openalex.org/W3101449015","https://openalex.org/W3105604018","https://openalex.org/W3126220825","https://openalex.org/W3133544351","https://openalex.org/W3169965252","https://openalex.org/W3200426230","https://openalex.org/W3203356073","https://openalex.org/W3207793743","https://openalex.org/W4353111936","https://openalex.org/W4367858557","https://openalex.org/W6637162671","https://openalex.org/W6640425456","https://openalex.org/W6685053522","https://openalex.org/W6728004082","https://openalex.org/W6744764900","https://openalex.org/W6746509016","https://openalex.org/W6757581960","https://openalex.org/W6758993734","https://openalex.org/W6767769423","https://openalex.org/W6769918834","https://openalex.org/W6780591833","https://openalex.org/W6783138424","https://openalex.org/W6801826067","https://openalex.org/W6803540780"],"related_works":["https://openalex.org/W4311734044","https://openalex.org/W3046843850","https://openalex.org/W2563096758","https://openalex.org/W4386716251","https://openalex.org/W4386053843","https://openalex.org/W4286899967","https://openalex.org/W3158004940","https://openalex.org/W3205128835","https://openalex.org/W4379258830","https://openalex.org/W4293092754"],"abstract_inverted_index":{"Hyperdimensional":[0],"(HD)":[1],"Computing":[2],"leverages":[3],"random":[4],"high":[5,17],"dimensional":[6,18],"vectors":[7],"(>10000":[8],"dimensions)":[9],"known":[10],"as":[11,179,181,257],"hypervectors":[12,50],"for":[13,42,131],"data":[14],"representation.":[15],"This":[16],"feature":[19],"representation":[20],"is":[21,96,161,232],"inherently":[22],"redundant":[23],"which":[24],"results":[25,184],"in":[26,60,85,215,265],"increased":[27],"robustness":[28,105,214,224],"against":[29,229,262],"noise":[30,178],"and":[31,56,110,123,140,143,151,239],"it":[32],"also":[33],"enables":[34],"the":[35,67,86,90,97,103,164,191,195,241,252],"use":[36],"of":[37,49,70,92,106,135,148,212,225,254],"a":[38,146,209,258],"computationally":[39],"simple":[40],"operations":[41],"all":[43],"vector":[44],"functions.":[45],"These":[46],"two":[47,132],"properties":[48],"have":[51],"led":[52],"to":[53,77,101,115,162,169,199,219,236,245],"energy":[54],"efficient":[55],"fast":[57],"learning":[58],"capabilities":[59],"numerous":[61],"Artificial":[62],"Intelligence":[63],"(AI)":[64],"applications.":[65],"Despite":[66],"increasing":[68],"number":[69],"such":[71,116],"AI":[72],"HD":[73,107,127,136,166,196,205,226,266],"applications,":[74],"their":[75,113],"susceptibility":[76],"adversarial":[78,104,155,187,213,255,263],"attacks":[79,192,231,238,264],"has":[80,240],"not":[81],"been":[82],"explored,":[83],"specifically":[84],"text":[87,108,129,141,220,268],"domain.":[88],"To":[89],"best":[91],"our":[93],"knowledge,":[94],"this":[95,119],"first":[98],"research":[99],"endeavour":[100],"evaluate":[102,251],"classifiers":[109,130,198,207,228],"report":[111],"on":[112],"vulnerability":[114],"attacks.":[117],"In":[118],"paper,":[120],"we":[121,250],"designed":[122],"developed":[124],"n-grams":[125],"based":[126],"computing":[128,167,197,206,227,267],"primary":[133],"applications":[134],"computing;":[137],"language":[138,216],"recognition":[139,217],"classification,":[142],"then":[144],"performed":[145],"set":[147],"character":[149],"level":[150,153],"word":[152],"grey-box":[154],"attacks,":[156],"where":[157],"an":[158],"attacker\u2019s":[159],"goal":[160],"mislead":[163,194],"target":[165],"classifier":[168],"produce":[170,200],"false":[171],"prediction":[172,202],"labels":[173],"while":[174],"keeping":[175],"added":[176],"perturbation":[177],"low":[180],"possible.":[182],"Our":[183],"show":[185,208],"that":[186],"examples":[188],"generated":[189],"by":[190],"can":[193],"incorrect":[201],"labels.":[203],"However,":[204],"higher":[210,234],"degree":[211],"compared":[218,235,244],"classification":[221],"tasks.":[222],"The":[223],"character-level":[230],"significantly":[233],"word-level":[237],"highest":[242],"accuracy":[243],"deep":[246],"learning-based":[247],"classifiers.":[248,269],"Finally,":[249],"effectiveness":[253],"training":[256],"possible":[259],"defense":[260],"strategy":[261]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}