{"id":"https://openalex.org/W2995147906","doi":null,"title":"Learning Stochastic Weight Masking to Resist Adversarial Attacks","display_name":"Learning Stochastic Weight Masking to Resist Adversarial Attacks","publication_year":2019,"publication_date":"2019-12-02","ids":{"openalex":"https://openalex.org/W2995147906","mag":"2995147906"},"language":"en","primary_location":{"id":"pmh:oai:dal.scholaris.ca:10222/76737","doi":null,"is_oa":false,"landing_page_url":"http://hdl.handle.net/10222/76737","pdf_url":null,"source":{"id":"https://openalex.org/S7407064432","display_name":"DalSpace (Dalhousie University)","issn_l":"2041-2096","issn":["2041-2096"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["dongbi-a","poland-140","russia-white-list-1"],"host_organization":"https://openalex.org/I129902397","host_organization_name":"Dalhousie University","host_organization_lineage":["https://openalex.org/I129902397"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"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/A5017547658","display_name":"Yoshimasa Kubo","orcid":"https://orcid.org/0009-0003-6882-4241","observed_orcids":["https://orcid.org/0009-0003-6882-4241"]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Yoshimasa Kubo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5017547658"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9994999766349792,"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":0.9994999766349792,"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/T10036","display_name":"Advanced Neural Network Applications","score":9.999999747378752e-05,"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"}},{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":0.0,"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/adversarial-examples","display_name":"adversarial examples","score":0.9539999961853027},{"id":"https://openalex.org/keywords/adversarial-attacks","display_name":"adversarial attacks","score":0.8299999833106995},{"id":"https://openalex.org/keywords/binary-neural-networks","display_name":"binary neural networks","score":0.8029999732971191},{"id":"https://openalex.org/keywords/overfitting","display_name":"overfitting","score":0.8109999895095825},{"id":"https://openalex.org/keywords/regularization","display_name":"regularization","score":0.9079999923706055},{"id":"https://openalex.org/keywords/gating-network","display_name":"gating network","score":0.4480000138282776},{"id":"https://openalex.org/keywords/white-box-attacks","display_name":"white-box attacks","score":0.6439999938011169},{"id":"https://openalex.org/keywords/black-box-attacks","display_name":"black-box attacks","score":1.0},{"id":"https://openalex.org/keywords/image-classification-robustness","display_name":"image classification robustness","score":0.6370000243186951},{"id":"https://openalex.org/keywords/activation-visualization","display_name":"activation visualization","score":0.6079999804496765}],"concepts":[{"id":"https://openalex.org/C53524968","wikidata":"https://www.wikidata.org/wiki/Q7315582","display_name":"Resist","level":3,"score":0.6770948171615601},{"id":"https://openalex.org/C2777402240","wikidata":"https://www.wikidata.org/wiki/Q6783436","display_name":"Masking (illustration)","level":2,"score":0.6400234699249268},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.6286870241165161},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5433467626571655},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.4160900115966797},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38876622915267944},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"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/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:dal.scholaris.ca:10222/76737","doi":null,"is_oa":false,"landing_page_url":"http://hdl.handle.net/10222/76737","pdf_url":null,"source":{"id":"https://openalex.org/S7407064432","display_name":"DalSpace (Dalhousie University)","issn_l":"2041-2096","issn":["2041-2096"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["dongbi-a","poland-140","russia-white-list-1"],"host_organization":"https://openalex.org/I129902397","host_organization_name":"Dalhousie University","host_organization_lineage":["https://openalex.org/I129902397"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null},{"id":"mag:2995147906","doi":null,"is_oa":false,"landing_page_url":"https://dalspace.library.dal.ca/handle/10222/76737","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W582134693","https://openalex.org/W639708223","https://openalex.org/W1533861849","https://openalex.org/W1686810756","https://openalex.org/W1932198206","https://openalex.org/W1967804600","https://openalex.org/W1982016364","https://openalex.org/W2019016101","https://openalex.org/W2064675550","https://openalex.org/W2072389508","https://openalex.org/W2108598243","https://openalex.org/W2119717200","https://openalex.org/W2130942839","https://openalex.org/W2136836265","https://openalex.org/W2143612262","https://openalex.org/W2145339207","https://openalex.org/W2147527908","https://openalex.org/W2161608691","https://openalex.org/W2184045248","https://openalex.org/W2194775991","https://openalex.org/W2200124539","https://openalex.org/W2243397390","https://openalex.org/W2247400071","https://openalex.org/W2260756217","https://openalex.org/W2279895976","https://openalex.org/W2408141691","https://openalex.org/W2486441166","https://openalex.org/W2504108613","https://openalex.org/W2516574342","https://openalex.org/W2543927648","https://openalex.org/W2551895583","https://openalex.org/W2562618250","https://openalex.org/W2570343428","https://openalex.org/W2604505099","https://openalex.org/W2604700561","https://openalex.org/W2606433045","https://openalex.org/W2620038827","https://openalex.org/W2728257130","https://openalex.org/W2746600820","https://openalex.org/W2749379418","https://openalex.org/W2766736793","https://openalex.org/W2774644650","https://openalex.org/W2787708942","https://openalex.org/W2795725650","https://openalex.org/W2949117887","https://openalex.org/W2951595529","https://openalex.org/W2962699575","https://openalex.org/W2963114950","https://openalex.org/W2963207607","https://openalex.org/W2964153729","https://openalex.org/W2964308564","https://openalex.org/W3022609240","https://openalex.org/W3118608800"],"related_works":["https://openalex.org/W2978447704","https://openalex.org/W2944839767","https://openalex.org/W2907582377","https://openalex.org/W3143105445","https://openalex.org/W3130999492","https://openalex.org/W2787733970","https://openalex.org/W7164327804","https://openalex.org/W7164713650","https://openalex.org/W3198031492","https://openalex.org/W7134196579"],"abstract_inverted_index":{"Adding":[0],"small":[1],"perturbations":[2],"to":[3,106,134,150,163,287,289,318,322],"test":[4,271],"images":[5],"can":[6,64],"drastically":[7],"change":[8],"the":[9,34,38,44,80,98,107,122,126,147,160,190,203,222,263,267,302,329,332],"classification":[10],"accuracy":[11],"of":[12,82,97,100,109,118,128,243,266,293,299,301,316,326,331],"machine":[13,53],"learning":[14,54],"models.":[15],"These":[16],"perturbed":[17],"examples":[18,22,29,69,130],"are":[19,253],"called":[20,202],"adversarial":[21,68,101,119,129,157,170,195],"(Szegedy":[23],"et":[24,57,71,111],"al.,":[25,58,72,112],"2013).":[26],"Studying":[27],"these":[28],"may":[30,76,335],"shed":[31],"light":[32],"on":[33,43,93,169,235,280],"learned":[35],"structure":[36],"in":[37,78,144,192,227,262],"network,":[39,248],"as":[40,42],"well":[41],"potential":[45],"security":[46],"threat":[47],"that":[48,113,174,224],"they":[49],"pose":[50],"for":[51],"practical":[52],"applications":[55],"(Kurakin":[56],"2016}.":[59],"Furthermore,":[60,197],"since":[61],"human":[62,83],"observers":[63],"be":[65,232],"fooled":[66],"by":[67],"(Elsayed":[70],"2018),":[73],"this":[74,87,138],"study":[75],"aid":[77],"preventing":[79],"manipulation":[81],"observers'":[84],"reactions.":[85],"In":[86,216],"thesis,":[88],"at":[89],"first,":[90],"we":[91,140,198,296,311],"focus":[92],"gaining":[94],"an":[95,291,324],"understanding":[96,292,325],"cause":[99,127],"examples.":[102,171],"We":[103,172,270],"argue,":[104],"adding":[105],"view":[108],"Galloway":[110],"overfitting":[114,186],"is":[115,131,149,162],"a":[116,200,218,244,313,319],"factor":[117],"examples,":[120],"while":[121],"other":[123],"researchers":[124],"found":[125],"not":[132,183],"related":[133,278],"overfitting.":[135],"To":[136],"make":[137],"argument,":[139],"include":[141],"two":[142],"directions":[143],"our":[145,274,294],"study,":[146],"first":[148],"evaluate":[151,164],"several":[152,277],"standard":[153],"regularization":[154],"techniques":[155],"with":[156,259,276],"attacks,":[158,285],"and":[159,212,249,256,272,283,286,306],"second":[161],"stochastic":[165,178],"binarized":[166,179,255],"neural":[167,180,247],"networks":[168,181,191],"report":[173],"strong":[175],"regularizations":[176],"including":[177],"do":[182],"only":[184],"improve":[185],"but":[187],"also":[188],"help":[189],"fighting":[193],"against":[194],"attacks.":[196],"introduce":[199],"model":[201,275],"Stochastic-Gated":[204],"Partially":[205],"Binarized":[206],"Network":[207],"(SGBN),":[208],"which":[209],"incorporates":[210],"binarization":[211],"input":[213],"dependent":[214],"stochasticity.":[215],"particular,":[217],"gate":[219,239,333],"module":[220,240],"learns":[221],"probability":[223],"individual":[225],"weights":[226],"corresponding":[228,260,308],"convolutional":[229,246,264],"filters":[230,261],"should":[231],"masked":[233],"(turned":[234],"or":[236],"off).":[237],"The":[238],"itself":[241],"consists":[242],"shallow":[245],"its":[250],"sigmoid":[251],"outputs":[252,305],"stochastically":[254],"pointwise":[257],"multiplied":[258],"layer":[265],"main":[268],"network.":[269],"compare":[273],"approaches":[279],"both":[281],"white-":[282],"black-box":[284],"try":[288],"gain":[290,323],"model,":[295],"visualize":[297],"activations":[298,330],"some":[300],"gating":[303],"network":[304],"their":[307],"filters.":[309],"Moreover,":[310],"apply":[312],"simple":[314],"version":[315],"SGBN":[317],"toy":[320],"experiment":[321],"how":[327],"changeable":[328],"modules":[334],"be.":[336]},"counts_by_year":[],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2019-12-26T00:00:00"}