{"id":"https://openalex.org/W3202573719","doi":"https://doi.org/10.1109/ijcnn52387.2021.9534154","title":"Targeted Attacks in Hierarchical Settings via Convex Programming","display_name":"Targeted Attacks in Hierarchical Settings via Convex Programming","publication_year":2021,"publication_date":"2021-07-18","ids":{"openalex":"https://openalex.org/W3202573719","doi":"https://doi.org/10.1109/ijcnn52387.2021.9534154","mag":"3202573719"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn52387.2021.9534154","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9534154","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","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/A5003538946","display_name":"Ismail Alkhouri","orcid":"https://orcid.org/0000-0002-5754-5509"},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ismail R. Alkhouri","raw_affiliation_strings":["University of Central Florida, Orlando, FL"],"affiliations":[{"raw_affiliation_string":"University of Central Florida, Orlando, FL","institution_ids":["https://openalex.org/I106165777"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003612688","display_name":"George Atia","orcid":"https://orcid.org/0000-0001-7958-9855"},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"George K. Atia","raw_affiliation_strings":["University of Central Florida, Orlando, FL"],"affiliations":[{"raw_affiliation_string":"University of Central Florida, Orlando, FL","institution_ids":["https://openalex.org/I106165777"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5003538946"],"corresponding_institution_ids":["https://openalex.org/I106165777"],"apc_list":null,"apc_paid":null,"fwci":0.136,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.55377442,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"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/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/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9751999974250793,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9362999796867371,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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":0.6240156292915344},{"id":"https://openalex.org/keywords/convex-optimization","display_name":"Convex optimization","score":0.4762292504310608},{"id":"https://openalex.org/keywords/regular-polygon","display_name":"Regular polygon","score":0.39621007442474365},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14369821548461914}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6240156292915344},{"id":"https://openalex.org/C157972887","wikidata":"https://www.wikidata.org/wiki/Q463359","display_name":"Convex optimization","level":3,"score":0.4762292504310608},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.39621007442474365},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14369821548461914},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn52387.2021.9534154","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9534154","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3736233273","display_name":null,"funder_award_id":"DE-EE0009152","funder_id":"https://openalex.org/F4320306084","funder_display_name":"U.S. Department of Energy"}],"funders":[{"id":"https://openalex.org/F4320306084","display_name":"U.S. Department of Energy","ror":"https://ror.org/01bj3aw27"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W1582706191","https://openalex.org/W1711649566","https://openalex.org/W1986080131","https://openalex.org/W2074295543","https://openalex.org/W2113642685","https://openalex.org/W2133665775","https://openalex.org/W2150766729","https://openalex.org/W2159778339","https://openalex.org/W2164278908","https://openalex.org/W2180612164","https://openalex.org/W2530123835","https://openalex.org/W2762718731","https://openalex.org/W2774644650","https://openalex.org/W2783784437","https://openalex.org/W2800244495","https://openalex.org/W2804549772","https://openalex.org/W2894990412","https://openalex.org/W2897494072","https://openalex.org/W2949979136","https://openalex.org/W2963178695","https://openalex.org/W2963857521","https://openalex.org/W2964043206","https://openalex.org/W2975486888","https://openalex.org/W2979878901","https://openalex.org/W2997293639","https://openalex.org/W2997532515","https://openalex.org/W3004478028","https://openalex.org/W3008313523","https://openalex.org/W3013520104","https://openalex.org/W3028070348","https://openalex.org/W3029455779","https://openalex.org/W3034488700","https://openalex.org/W3090857213","https://openalex.org/W3094304065","https://openalex.org/W3103940881","https://openalex.org/W3161111820","https://openalex.org/W4245534220","https://openalex.org/W4292363360","https://openalex.org/W4297825594","https://openalex.org/W4394644156","https://openalex.org/W6696497002","https://openalex.org/W6727970316","https://openalex.org/W6774127024","https://openalex.org/W6795266579","https://openalex.org/W6864546407"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W4402327032","https://openalex.org/W3153752017"],"abstract_inverted_index":{"Adversarial":[0],"attacks":[1,96,124],"were":[2],"shown":[3,90,113],"to":[4,34,42,53,63,91,122],"drastically":[5],"degrade":[6],"the":[7,20,58,79,126],"performance":[8],"of":[9,22,60,83,137],"one-stage":[10],"classifiers":[11],"while":[12],"being":[13],"undetectable.":[14],"In":[15],"this":[16],"paper,":[17],"we":[18],"examine":[19],"susceptibility":[21],"both":[23],"flat":[24],"and":[25,31,88,100,109],"top-down":[26],"hierarchical":[27],"classifiers,":[28],"abbreviated":[29],"FHCs":[30,99,115],"TDHCs":[32,101,121],"respectively,":[33],"targeted":[35],"adversarial":[36],"attacks.":[37],"Convex":[38],"programs":[39],"are":[40,102,116],"formulated":[41],"generate":[43],"input":[44],"perturbations":[45],"geared":[46],"at":[47],"altering":[48],"their":[49,106,130],"output":[50],"predictions":[51],"according":[52],"pre-specified":[54],"targets":[55],"(e.g.,":[56],"changing":[57],"prediction":[59],"a":[61,64,68],"\u2018cat\u2019":[62],"\u2018car\u2019":[65],"rather":[66],"than":[67,120],"\u2018dog\u2019":[69],"or":[70],"some":[71],"other":[72],"pet).":[73],"A":[74],"competitive":[75],"solver":[76],"based":[77,104],"on":[78,105],"Alternating":[80],"Direction":[81],"Method":[82],"Multipliers":[84],"(ADMM)":[85],"is":[86,89,112],"developed":[87,97],"outperform":[92],"state-of-the-art":[93],"solvers.":[94],"The":[95],"for":[98],"evaluated":[103],"success":[107],"rate":[108],"imperceptibility.":[110],"It":[111],"that":[114,128],"inherently":[117],"more":[118],"robust":[119],"said":[123],"in":[125],"sense":[127],"fooling":[129],"coarse":[131],"classification":[132],"generally":[133],"requires":[134],"higher":[135],"levels":[136],"perturbation.":[138]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}