{"id":"https://openalex.org/W3125827990","doi":"https://doi.org/10.1109/globecom42002.2020.9322088","title":"Evaluating and Improving Adversarial Attacks on DNN-Based Modulation Recognition","display_name":"Evaluating and Improving Adversarial Attacks on DNN-Based Modulation Recognition","publication_year":2020,"publication_date":"2020-12-01","ids":{"openalex":"https://openalex.org/W3125827990","doi":"https://doi.org/10.1109/globecom42002.2020.9322088","mag":"3125827990"},"language":"en","primary_location":{"id":"doi:10.1109/globecom42002.2020.9322088","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom42002.2020.9322088","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2020 - 2020 IEEE Global Communications Conference","raw_type":"proceedings-article"},"type":"conference-paper","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/A5070909438","display_name":"Haojun Zhao","orcid":"https://orcid.org/0000-0003-2578-9733"},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haojun Zhao","raw_affiliation_strings":["College of Information and Communication Engineering, Harbin Engineering University, Harbin, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information and Communication Engineering, Harbin Engineering University, Harbin, P. R. China","institution_ids":["https://openalex.org/I151727225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100778980","display_name":"Yun Lin","orcid":"https://orcid.org/0000-0002-4002-1282"},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yun Lin","raw_affiliation_strings":["College of Information and Communication Engineering, Harbin Engineering University, Harbin, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information and Communication Engineering, Harbin Engineering University, Harbin, P. R. China","institution_ids":["https://openalex.org/I151727225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102814071","display_name":"Song Gao","orcid":"https://orcid.org/0000-0002-7169-6370"},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Song Gao","raw_affiliation_strings":["National Pilot School of Software, Yunnan University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Pilot School of Software, Yunnan University, China","institution_ids":["https://openalex.org/I189210763"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005228053","display_name":"Shui Yu","orcid":"https://orcid.org/0000-0003-4485-6743"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Shui Yu","raw_affiliation_strings":["School of Computer Science, University of Technology Sydney, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Technology Sydney, Australia","institution_ids":["https://openalex.org/I114017466"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":38,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9990000128746033,"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":0.9990000128746033,"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/T11515","display_name":"Bacillus and Francisella bacterial research","score":0.9769999980926514,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T14117","display_name":"Integrated Circuits and Semiconductor Failure Analysis","score":0.968999981880188,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.700173556804657},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.6741472482681274},{"id":"https://openalex.org/keywords/invisibility","display_name":"Invisibility","score":0.5856316685676575},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5478321313858032},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.541702926158905},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5031270384788513},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.49659019708633423},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.4949154257774353},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4736967086791992},{"id":"https://openalex.org/keywords/waveform","display_name":"Waveform","score":0.443695992231369},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4305557906627655},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41140851378440857},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3483346700668335},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10563856363296509},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.08539095520973206}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.700173556804657},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.6741472482681274},{"id":"https://openalex.org/C50962388","wikidata":"https://www.wikidata.org/wiki/Q762018","display_name":"Invisibility","level":2,"score":0.5856316685676575},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5478321313858032},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.541702926158905},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5031270384788513},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.49659019708633423},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.4949154257774353},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4736967086791992},{"id":"https://openalex.org/C197424946","wikidata":"https://www.wikidata.org/wiki/Q1165717","display_name":"Waveform","level":3,"score":0.443695992231369},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4305557906627655},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41140851378440857},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3483346700668335},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10563856363296509},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.08539095520973206},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/globecom42002.2020.9322088","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom42002.2020.9322088","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2020 - 2020 IEEE Global Communications Conference","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.41999998688697815,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321939","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1945616565","https://openalex.org/W2180612164","https://openalex.org/W2460937040","https://openalex.org/W2562146178","https://openalex.org/W2640329709","https://openalex.org/W2765424254","https://openalex.org/W2773170971","https://openalex.org/W2774644650","https://openalex.org/W2888024549","https://openalex.org/W2903382683","https://openalex.org/W2908997014","https://openalex.org/W2963207607","https://openalex.org/W2963857521","https://openalex.org/W2964121744","https://openalex.org/W2964153729","https://openalex.org/W2964253222","https://openalex.org/W2966579212","https://openalex.org/W2968867107","https://openalex.org/W3103557498","https://openalex.org/W4293846201","https://openalex.org/W4300511536","https://openalex.org/W6631190155","https://openalex.org/W6637162671","https://openalex.org/W6640425456","https://openalex.org/W6719080892","https://openalex.org/W6730655975","https://openalex.org/W6757107679","https://openalex.org/W6757355660"],"related_works":["https://openalex.org/W2950183588","https://openalex.org/W3080754722","https://openalex.org/W3093978547","https://openalex.org/W2953536436","https://openalex.org/W3203790781","https://openalex.org/W4313346231","https://openalex.org/W2738001131","https://openalex.org/W4285785480","https://openalex.org/W2997056298","https://openalex.org/W4298079292"],"abstract_inverted_index":{"The":[0],"discovery":[1],"of":[2,41,53,63,70,75,81,142,152],"adversarial":[3,48,111],"examples":[4],"poses":[5],"a":[6,17,27,92,101,131,145],"serious":[7],"risk":[8,151],"to":[9,23,94,109,144],"the":[10,24,38,42,51,60,64,68,72,79,88,96,104,116,138,150],"deep":[11],"neural":[12],"networks":[13],"(DNN).":[14],"By":[15],"adding":[16],"subtle":[18],"perturbation":[19],"that":[20,115],"is":[21],"imperceptible":[22],"human":[25],"eye,":[26],"well-behaved":[28],"DNN":[29],"model":[30],"can":[31,127],"be":[32],"easily":[33],"fooled":[34],"and":[35,99],"completely":[36],"change":[37],"prediction":[39,61],"categories":[40],"input":[43],"samples.":[44],"However,":[45],"research":[46],"on":[47,58,130],"attacks":[49,124,129,143],"in":[50],"field":[52],"modulation":[54,83],"recognition":[55],"mainly":[56],"focuses":[57],"increasing":[59],"error":[62],"classifier,":[65],"while":[66],"ignores":[67],"importance":[69],"decreasing":[71],"perceptual":[73,140],"invisibility":[74,141],"attack.":[76],"Aiming":[77],"at":[78],"task":[80],"DNNbased":[82],"recognition,":[84],"this":[85],"study":[86],"designs":[87],"Fitting":[89],"Difference":[90],"as":[91],"metric":[93],"measure":[95],"perturbed":[97],"waveforms":[98],"proposes":[100],"new":[102],"method:":[103],"Nesterov":[105],"Adam":[106],"Iterative":[107],"Method":[108],"generate":[110],"examples.":[112],"We":[113],"show":[114],"proposed":[117],"algorithm":[118],"not":[119],"only":[120],"exerts":[121],"excellent":[122],"white-box":[123],"but":[125],"also":[126],"initiate":[128],"black-box":[132],"model.":[133],"Moreover,":[134],"our":[135],"method":[136],"decreases":[137],"waveform":[139],"certain":[146],"degree,":[147],"thereby":[148],"reducing":[149],"an":[153],"attack":[154],"being":[155],"detected.":[156]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":14},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
