{"id":"https://openalex.org/W3007322186","doi":"https://doi.org/10.1109/icassp40776.2020.9053342","title":"Enhanced Adversarial Strategically-Timed Attacks Against Deep Reinforcement Learning","display_name":"Enhanced Adversarial Strategically-Timed Attacks Against Deep Reinforcement Learning","publication_year":2020,"publication_date":"2020-04-09","ids":{"openalex":"https://openalex.org/W3007322186","doi":"https://doi.org/10.1109/icassp40776.2020.9053342","mag":"3007322186"},"language":"en","primary_location":{"id":"doi:10.1109/icassp40776.2020.9053342","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9053342","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2002.09027.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5020376803","display_name":"Chao-Han Huck Yang","orcid":"https://orcid.org/0000-0003-2879-8811"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chao-Han Huck Yang","raw_affiliation_strings":["Georgia Institute of Technology, Atlanta, GA, USA","Georgia Institute of Technology, Atlanta, GA (USA)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]},{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, GA (USA)","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042520842","display_name":"Jun Qi","orcid":"https://orcid.org/0000-0001-7533-2630"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jun Qi","raw_affiliation_strings":["Georgia Institute of Technology, Atlanta, GA, USA","Georgia Institute of Technology, Atlanta, GA (USA)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]},{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, GA (USA)","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050344371","display_name":"Pin\u2010Yu Chen","orcid":"https://orcid.org/0000-0003-1039-8369"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pin-Yu Chen","raw_affiliation_strings":["IBM Research, NY, USA","IBM Res., NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research, NY, USA","institution_ids":["https://openalex.org/I1341412227"]},{"raw_affiliation_string":"IBM Res., NY, USA","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103563165","display_name":"Yi Ouyang","orcid":"https://orcid.org/0000-0003-0835-5722"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yi Ouyang","raw_affiliation_strings":["Preferred Network America, Berkeley, CA, USA","Preferred Network America,Berkeley,CA,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Preferred Network America, Berkeley, CA, USA","institution_ids":[]},{"raw_affiliation_string":"Preferred Network America,Berkeley,CA,USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017253829","display_name":"I-Te Danny Hung","orcid":null},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"I-Te Danny Hung","raw_affiliation_strings":["Columbia University, NY","Columbia Univ, NY"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Columbia University, NY","institution_ids":["https://openalex.org/I78577930"]},{"raw_affiliation_string":"Columbia Univ, NY","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066868860","display_name":"Chin\u2010Hui Lee","orcid":"https://orcid.org/0000-0002-1892-2551"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chin-Hui Lee","raw_affiliation_strings":["Georgia Institute of Technology, Atlanta, GA, USA","Georgia Institute of Technology, Atlanta, GA (USA)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]},{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, GA (USA)","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001706958","display_name":"Xiaoli Ma","orcid":"https://orcid.org/0000-0002-3076-2589"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaoli Ma","raw_affiliation_strings":["Georgia Institute of Technology, Atlanta, GA, USA","Georgia Institute of Technology, Atlanta, GA (USA)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]},{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, GA (USA)","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3407","last_page":"3411"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9993000030517578,"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":0.9993000030517578,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9563000202178955,"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/T10800","display_name":"Forensic Toxicology and Drug Analysis","score":0.9361000061035156,"subfield":{"id":"https://openalex.org/subfields/3005","display_name":"Toxicology"},"field":{"id":"https://openalex.org/fields/30","display_name":"Pharmacology, Toxicology and Pharmaceutics"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.7831624746322632},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.7713881731033325},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.703505277633667},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6480664610862732},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.5403251051902771},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.48712635040283203},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.4690476059913635},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.44002580642700195},{"id":"https://openalex.org/keywords/adversarial-machine-learning","display_name":"Adversarial machine learning","score":0.43891507387161255},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3987475335597992}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.7831624746322632},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7713881731033325},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.703505277633667},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6480664610862732},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.5403251051902771},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.48712635040283203},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4690476059913635},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44002580642700195},{"id":"https://openalex.org/C2778403875","wikidata":"https://www.wikidata.org/wiki/Q20312394","display_name":"Adversarial machine learning","level":3,"score":0.43891507387161255},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3987475335597992},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/icassp40776.2020.9053342","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9053342","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},{"id":"mag:3007322186","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/2002.09027.pdf","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.2002.09027","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2002.09027","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":"article-journal"},{"id":"doi:10.17023/aaf8-4x88","is_oa":true,"landing_page_url":"https://doi.org/10.17023/aaf8-4x88","pdf_url":null,"source":{"id":"https://openalex.org/S7407051697","display_name":"IEEE RESOURCE CENTERS","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":"Audiovisual"}],"best_oa_location":{"id":"mag:3007322186","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/2002.09027.pdf","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},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1508882636","https://openalex.org/W1580779066","https://openalex.org/W2089106098","https://openalex.org/W2137104525","https://openalex.org/W2145339207","https://openalex.org/W2602963933","https://openalex.org/W2746600820","https://openalex.org/W2795727551","https://openalex.org/W2884634491","https://openalex.org/W2889987506","https://openalex.org/W2905342215","https://openalex.org/W2914261249","https://openalex.org/W2924168890","https://openalex.org/W2941205169","https://openalex.org/W2949103145","https://openalex.org/W2952603690","https://openalex.org/W2960644152","https://openalex.org/W2963207607","https://openalex.org/W2964043796","https://openalex.org/W2970027712","https://openalex.org/W6630417872","https://openalex.org/W6640425456","https://openalex.org/W6692846177","https://openalex.org/W6733049761","https://openalex.org/W6735677848","https://openalex.org/W6753526802","https://openalex.org/W6753596642","https://openalex.org/W6757988111","https://openalex.org/W6758978475","https://openalex.org/W6765977438"],"related_works":["https://openalex.org/W3163651025","https://openalex.org/W3136258283","https://openalex.org/W3187464208","https://openalex.org/W2019357403","https://openalex.org/W3029964298","https://openalex.org/W2949384876","https://openalex.org/W3022473380","https://openalex.org/W2883567023","https://openalex.org/W2765450862","https://openalex.org/W3201133495","https://openalex.org/W2891963093","https://openalex.org/W3025050900","https://openalex.org/W3048433359","https://openalex.org/W2946524641","https://openalex.org/W3048753943","https://openalex.org/W3094044835","https://openalex.org/W3007935884","https://openalex.org/W3131738409","https://openalex.org/W2982312374","https://openalex.org/W3034493393"],"abstract_inverted_index":{"Recent":[0],"deep":[1,20],"neural":[2],"networks":[3],"based":[4,116],"techniques,":[5],"especially":[6],"those":[7],"equipped":[8],"with":[9],"the":[10,15,44,48,55,90,96,133,144,158,162],"ability":[11],"of":[12,30,57,98,160,164],"self-adaptation":[13],"in":[14,85],"system":[16,82],"level":[17],"such":[18],"as":[19],"reinforcement":[21],"learning":[22,33,124,166],"(DRL),":[23],"are":[24,129],"shown":[25],"to":[26,110,131,150],"possess":[27],"many":[28],"advantages":[29],"optimizing":[31],"robot":[32,40,123,165],"systems":[34,46],"(e.g.,":[35,60],"autonomous":[36],"navigation":[37,81,100,126],"and":[38,47,64,125,155],"continuous":[39],"arm":[41],"control.)":[42],"However,":[43],"learning-based":[45,99],"associated":[49],"models":[50],"may":[51],"be":[52],"threatened":[53],"by":[54,83],"risks":[56],"intentionally":[58],"adaptive":[59],"noisy":[61],"sensor":[62],"confusion)":[63],"adversarial":[65,76,105,136,145],"perturbations":[66],"from":[67],"real-world":[68],"scenarios.":[69],"In":[70],"this":[71],"paper,":[72],"we":[73,102],"introduce":[74],"timing-based":[75],"strategies":[77],"against":[78],"a":[79,151],"DRL-based":[80],"jamming":[84],"physical":[86],"noise":[87],"patterns":[88],"on":[89,117],"selected":[91],"time":[92],"frames.":[93],"To":[94],"study":[95,132],"vulnerability":[97,134],"systems,":[101],"propose":[103],"two":[104],"agent":[106],"models:":[107],"one":[108,114],"refers":[109],"online":[111],"learning;":[112],"another":[113],"is":[115],"evolutionary":[118],"learning.":[119],"Besides,":[120],"three":[121],"open-source":[122],"control":[127],"environments":[128],"employed":[130],"under":[135],"timing":[137,146],"attacks.":[138],"Our":[139],"experimental":[140],"results":[141],"show":[142],"that":[143],"attacks":[147],"can":[148],"lead":[149],"significant":[152],"performance":[153],"drop,":[154],"also":[156],"suggest":[157],"necessity":[159],"enhancing":[161],"robustness":[163],"systems.":[167]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
