{"id":"https://openalex.org/W4390693543","doi":"https://doi.org/10.1109/iccais59597.2023.10382270","title":"Uncovering the Resilience of Binarized Spiking Neural Networks under Adversarial Attacks","display_name":"Uncovering the Resilience of Binarized Spiking Neural Networks under Adversarial Attacks","publication_year":2023,"publication_date":"2023-11-27","ids":{"openalex":"https://openalex.org/W4390693543","doi":"https://doi.org/10.1109/iccais59597.2023.10382270"},"language":"en","primary_location":{"id":"doi:10.1109/iccais59597.2023.10382270","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/iccais59597.2023.10382270","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 12th International Conference on Control, Automation and Information Sciences (ICCAIS)","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/A5041044792","display_name":"Ngoc-My Bui","orcid":null},"institutions":[{"id":"https://openalex.org/I64519617","display_name":"Hanoi University","ror":"https://ror.org/01mxx0e62","country_code":"VN","type":"education","lineage":["https://openalex.org/I64519617"]}],"countries":["VN"],"is_corresponding":true,"raw_author_name":"Ngoc-My Bui","raw_affiliation_strings":["AMST,Hanoi,Vietnam","AMST, Hanoi, Vietnam"],"affiliations":[{"raw_affiliation_string":"AMST,Hanoi,Vietnam","institution_ids":["https://openalex.org/I64519617"]},{"raw_affiliation_string":"AMST, Hanoi, Vietnam","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026761479","display_name":"Van-Ngoc Dinh","orcid":"https://orcid.org/0000-0002-0525-8102"},"institutions":[{"id":"https://openalex.org/I64519617","display_name":"Hanoi University","ror":"https://ror.org/01mxx0e62","country_code":"VN","type":"education","lineage":["https://openalex.org/I64519617"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Van-Ngoc Dinh","raw_affiliation_strings":["AMST,Hanoi,Vietnam","AMST, Hanoi, Vietnam"],"affiliations":[{"raw_affiliation_string":"AMST,Hanoi,Vietnam","institution_ids":["https://openalex.org/I64519617"]},{"raw_affiliation_string":"AMST, Hanoi, Vietnam","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045030863","display_name":"Van-Hau Pham","orcid":"https://orcid.org/0000-0003-3147-3356"},"institutions":[{"id":"https://openalex.org/I64519617","display_name":"Hanoi University","ror":"https://ror.org/01mxx0e62","country_code":"VN","type":"education","lineage":["https://openalex.org/I64519617"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Van-Hau Pham","raw_affiliation_strings":["AMST,Hanoi,Vietnam","AMST, Hanoi, Vietnam"],"affiliations":[{"raw_affiliation_string":"AMST,Hanoi,Vietnam","institution_ids":["https://openalex.org/I64519617"]},{"raw_affiliation_string":"AMST, Hanoi, Vietnam","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006058636","display_name":"Quang\u2010Kien Trinh","orcid":"https://orcid.org/0000-0002-0499-2938"},"institutions":[{"id":"https://openalex.org/I131359167","display_name":"Le Quy Don Technical University","ror":"https://ror.org/04wgyjv21","country_code":"VN","type":"education","lineage":["https://openalex.org/I131359167"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Quang-Kien Trinh","raw_affiliation_strings":["Le Quy Don Technical University,Hanoi,Vietnam","Le Quy Don Technical University, Hanoi, Vietnam"],"affiliations":[{"raw_affiliation_string":"Le Quy Don Technical University,Hanoi,Vietnam","institution_ids":["https://openalex.org/I131359167"]},{"raw_affiliation_string":"Le Quy Don Technical University, Hanoi, Vietnam","institution_ids":["https://openalex.org/I131359167"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5041044792"],"corresponding_institution_ids":["https://openalex.org/I64519617"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1764909,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"674","last_page":"679"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","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/T10502","display_name":"Advanced Memory and Neural Computing","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/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.9987000226974487,"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":0.9968000054359436,"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-system","display_name":"Adversarial system","score":0.8529492616653442},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.8104397058486938},{"id":"https://openalex.org/keywords/mnist-database","display_name":"MNIST database","score":0.8083112835884094},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7750778794288635},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6535886526107788},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6472170352935791},{"id":"https://openalex.org/keywords/spiking-neural-network","display_name":"Spiking neural network","score":0.5903449654579163},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.5902494788169861},{"id":"https://openalex.org/keywords/resilience","display_name":"Resilience (materials science)","score":0.5724282264709473},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.49575552344322205}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.8529492616653442},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.8104397058486938},{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.8083112835884094},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7750778794288635},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6535886526107788},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6472170352935791},{"id":"https://openalex.org/C11731999","wikidata":"https://www.wikidata.org/wiki/Q9067355","display_name":"Spiking neural network","level":3,"score":0.5903449654579163},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.5902494788169861},{"id":"https://openalex.org/C2779585090","wikidata":"https://www.wikidata.org/wiki/Q3457762","display_name":"Resilience (materials science)","level":2,"score":0.5724282264709473},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.49575552344322205},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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/iccais59597.2023.10382270","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/iccais59597.2023.10382270","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 12th International Conference on Control, Automation and Information Sciences (ICCAIS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W47480302","https://openalex.org/W1673923490","https://openalex.org/W1686810756","https://openalex.org/W2098470668","https://openalex.org/W2300242332","https://openalex.org/W2513853720","https://openalex.org/W2523246573","https://openalex.org/W2750384547","https://openalex.org/W2963542245","https://openalex.org/W2964304804","https://openalex.org/W2978279179","https://openalex.org/W2984844508","https://openalex.org/W3037354233","https://openalex.org/W3093729901","https://openalex.org/W3097285691","https://openalex.org/W3107320086","https://openalex.org/W3197327073","https://openalex.org/W3212071010","https://openalex.org/W3213073654","https://openalex.org/W4206552843","https://openalex.org/W4293846201","https://openalex.org/W4308274240","https://openalex.org/W4309156448","https://openalex.org/W6637162671","https://openalex.org/W6637373629","https://openalex.org/W6640425456","https://openalex.org/W6727249380","https://openalex.org/W6743688258","https://openalex.org/W6771809012"],"related_works":["https://openalex.org/W4281699635","https://openalex.org/W4321472116","https://openalex.org/W3202619090","https://openalex.org/W3102040318","https://openalex.org/W4287724471","https://openalex.org/W3214713078","https://openalex.org/W2786930404","https://openalex.org/W3161396968","https://openalex.org/W3035000326","https://openalex.org/W2944910788"],"abstract_inverted_index":{"The":[0],"Binarized":[1],"Spiking":[2,6],"Neural":[3,7,42],"Network":[4,8],"(BSNN)-a":[5],"with":[9],"binary":[10],"weights,":[11],"is":[12],"particularly":[13],"suitable":[14],"for":[15],"Edge-AI":[16],"hardware":[17],"architectures":[18],"thanks":[19],"to":[20,53,95,114,125],"its":[21,126],"simplicity":[22],"in":[23,129],"data":[24],"format":[25],"and":[26,76,92],"computing":[27],"functions.":[28],"However,":[29],"like":[30],"other":[31],"SNNs,":[32],"BSNNs":[33,64,73,109],"could":[34],"be":[35],"directly":[36],"trained":[37],"or":[38],"converted":[39],"from":[40],"Artificial":[41],"Networks":[43],"using":[44],"the":[45,61,70,80,86,96,106,115,119],"gradient":[46],"principle.":[47],"They":[48],"hence":[49],"are":[50],"highly":[51],"susceptible":[52],"adversarial":[54,66,90,102,111],"attacks.":[55,67],"This":[56,83],"study":[57],"focuses":[58],"on":[59,79],"investigating":[60],"resilience":[62,120],"of":[63,72,89,108,121],"against":[65,110],"We":[68],"assess":[69],"robustness":[71,107],"through":[74],"FGSM":[75],"PGD":[77],"attacks":[78,112],"Fashion-MNIST":[81],"dataset.":[82],"work":[84],"marks":[85],"first":[87],"implementation":[88],"attack":[91],"defense":[93],"tailored":[94],"BSNNs.":[97],"Our":[98],"results":[99],"show":[100],"that":[101],"training":[103],"significantly":[104],"enhances":[105],"compared":[113],"original":[116],"model.":[117],"Improving":[118],"BSNN":[122],"opens":[123],"doors":[124],"potential":[127],"applications":[128],"real-world":[130],"scenarios.":[131]},"counts_by_year":[],"updated_date":"2025-12-25T23:11:45.687758","created_date":"2025-10-10T00:00:00"}
