{"id":"https://openalex.org/W2969337066","doi":"https://doi.org/10.1145/3415048.3416103","title":"A Statistical Defense Approach for Detecting Adversarial Examples","display_name":"A Statistical Defense Approach for Detecting Adversarial Examples","publication_year":2020,"publication_date":"2020-07-30","ids":{"openalex":"https://openalex.org/W2969337066","doi":"https://doi.org/10.1145/3415048.3416103","mag":"2969337066"},"language":"en","primary_location":{"id":"doi:10.1145/3415048.3416103","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3415048.3416103","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 International Conference on Pattern Recognition and Intelligent Systems","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1908.09705","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5051071107","display_name":"Alessandro Cennamo","orcid":"https://orcid.org/0000-0001-6475-1354"},"institutions":[{"id":"https://openalex.org/I167360494","display_name":"University of Wuppertal","ror":"https://ror.org/00613ak93","country_code":"DE","type":"education","lineage":["https://openalex.org/I167360494"]},{"id":"https://openalex.org/I4210130520","display_name":"Aptiv (Germany)","ror":"https://ror.org/039sb8791","country_code":"DE","type":"company","lineage":["https://openalex.org/I4210107152","https://openalex.org/I4210130520"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Alessandro Cennamo","raw_affiliation_strings":["Aptiv Services Deutschland GmbH, University of Wuppertal (BUW), Wuppertal, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Aptiv Services Deutschland GmbH, University of Wuppertal (BUW), Wuppertal, Germany","institution_ids":["https://openalex.org/I167360494","https://openalex.org/I4210130520"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016663410","display_name":"Ido Freeman","orcid":"https://orcid.org/0000-0003-4825-060X"},"institutions":[{"id":"https://openalex.org/I167360494","display_name":"University of Wuppertal","ror":"https://ror.org/00613ak93","country_code":"DE","type":"education","lineage":["https://openalex.org/I167360494"]},{"id":"https://openalex.org/I4210130520","display_name":"Aptiv (Germany)","ror":"https://ror.org/039sb8791","country_code":"DE","type":"company","lineage":["https://openalex.org/I4210107152","https://openalex.org/I4210130520"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Ido Freeman","raw_affiliation_strings":["Aptiv Services Deutschland GmbH, University of Wuppertal (BUW), Wuppertal, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Aptiv Services Deutschland GmbH, University of Wuppertal (BUW), Wuppertal, Germany","institution_ids":["https://openalex.org/I167360494","https://openalex.org/I4210130520"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080666933","display_name":"Anton Kummert","orcid":"https://orcid.org/0000-0002-0282-5087"},"institutions":[{"id":"https://openalex.org/I167360494","display_name":"University of Wuppertal","ror":"https://ror.org/00613ak93","country_code":"DE","type":"education","lineage":["https://openalex.org/I167360494"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Anton Kummert","raw_affiliation_strings":["University of Wuppertal (BUW), Wuppertal, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Wuppertal (BUW), Wuppertal, Germany","institution_ids":["https://openalex.org/I167360494"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":1.0,"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":1.0,"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/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9861999750137329,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.9596999883651733,"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":0.83366858959198},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7848246693611145},{"id":"https://openalex.org/keywords/statistic","display_name":"Statistic","score":0.6756118535995483},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6665533781051636},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6436843872070312},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5180273652076721},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4967702031135559},{"id":"https://openalex.org/keywords/signature","display_name":"Signature (topology)","score":0.4839940071105957},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.48190954327583313},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4663715958595276},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4551827609539032},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4406552016735077},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4297904372215271},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.42472654581069946},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3846195936203003},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12281748652458191},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07811686396598816}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.83366858959198},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7848246693611145},{"id":"https://openalex.org/C89128539","wikidata":"https://www.wikidata.org/wiki/Q1949963","display_name":"Statistic","level":2,"score":0.6756118535995483},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6665533781051636},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6436843872070312},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5180273652076721},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4967702031135559},{"id":"https://openalex.org/C2779696439","wikidata":"https://www.wikidata.org/wiki/Q7512811","display_name":"Signature (topology)","level":2,"score":0.4839940071105957},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48190954327583313},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4663715958595276},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4551827609539032},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4406552016735077},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4297904372215271},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.42472654581069946},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3846195936203003},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12281748652458191},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07811686396598816},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1145/3415048.3416103","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3415048.3416103","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 International Conference on Pattern Recognition and Intelligent Systems","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1908.09705","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1908.09705","pdf_url":"https://arxiv.org/pdf/1908.09705","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"mag:2969337066","is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/1908.09705","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1908.09705","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1908.09705","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1908.09705","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1908.09705","pdf_url":"https://arxiv.org/pdf/1908.09705","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2969337066.pdf","grobid_xml":"https://content.openalex.org/works/W2969337066.grobid-xml"},"referenced_works_count":29,"referenced_works":["https://openalex.org/W1932198206","https://openalex.org/W1945616565","https://openalex.org/W2117876524","https://openalex.org/W2119112357","https://openalex.org/W2230740169","https://openalex.org/W2243397390","https://openalex.org/W2346735539","https://openalex.org/W2469609794","https://openalex.org/W2581082771","https://openalex.org/W2607219512","https://openalex.org/W2618043096","https://openalex.org/W2746600820","https://openalex.org/W2774018344","https://openalex.org/W2774644650","https://openalex.org/W2795098699","https://openalex.org/W2953248129","https://openalex.org/W2963098487","https://openalex.org/W2963207607","https://openalex.org/W2963389226","https://openalex.org/W2963542245","https://openalex.org/W2963744840","https://openalex.org/W2963857521","https://openalex.org/W2964153729","https://openalex.org/W3118608800","https://openalex.org/W6637162671","https://openalex.org/W6689238212","https://openalex.org/W6719080892","https://openalex.org/W6729756640","https://openalex.org/W6758975236"],"related_works":["https://openalex.org/W3085730980","https://openalex.org/W2972262177","https://openalex.org/W3170633914","https://openalex.org/W3205795361","https://openalex.org/W2598549816","https://openalex.org/W2897163316","https://openalex.org/W3129673631","https://openalex.org/W2993903663","https://openalex.org/W3041676721","https://openalex.org/W3002676788","https://openalex.org/W3046957164","https://openalex.org/W3090897510","https://openalex.org/W3111893669","https://openalex.org/W2998277219","https://openalex.org/W3120472682","https://openalex.org/W3195497129","https://openalex.org/W3022481035","https://openalex.org/W3006896454","https://openalex.org/W2964283260","https://openalex.org/W2787710446"],"abstract_inverted_index":{"Adversarial":[0],"examples":[1],"are":[2],"maliciously":[3],"modified":[4],"inputs":[5,17],"created":[6],"to":[7,22,33,82,101,115,138],"fool":[8],"Machine":[9],"Learning":[10],"algorithms":[11],"(ML).":[12],"The":[13,106],"existence":[14],"of":[15,25,51,55,72],"such":[16],"presents":[18],"a":[19,52,84,97],"major":[20],"issue":[21],"the":[23,34,49,64,73,78,88,92,103,110,117],"expansion":[24],"ML-based":[26],"solutions.":[27,141],"Many":[28],"researchers":[29],"have":[30],"already":[31],"contributed":[32],"topic,":[35],"providing":[36],"both":[37],"cutting":[38],"edge-attack":[39],"techniques":[40],"and":[41],"various":[42,133],"defense":[43,140],"strategies.":[44],"This":[45],"work":[46],"focuses":[47],"on":[48],"development":[50],"system":[53],"capable":[54],"detecting":[56],"adversarial":[57],"samples":[58],"by":[59],"exploiting":[60],"statistical":[61],"information":[62],"from":[63],"training-set.":[65],"Our":[66],"detector":[67],"computes":[68],"several":[69],"distorted":[70],"replicas":[71],"test":[74],"input,":[75],"then":[76],"collects":[77],"classifier's":[79],"prediction":[80],"vectors":[81],"build":[83],"meaningful":[85],"signature":[86,93],"for":[87,109],"detection":[89],"task.":[90],"Then,":[91],"is":[94,113],"projected":[95],"onto":[96],"class-specific":[98],"statistic":[99],"vector":[100],"infer":[102],"input's":[104],"nature.":[105],"class":[107],"predicted":[108],"original":[111],"input":[112],"used":[114],"select":[116],"class-statistic":[118],"vector.":[119],"We":[120],"show":[121],"that":[122],"our":[123],"method":[124],"reliably":[125],"detects":[126],"malicious":[127],"inputs,":[128],"outperforming":[129],"state-of-the-art":[130],"approaches":[131],"in":[132],"settings,":[134],"while":[135],"being":[136],"complementary":[137],"other":[139]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
