{"id":"https://openalex.org/W4392175341","doi":"https://doi.org/10.1109/globecom54140.2023.10437779","title":"Backdoor Attacks on Multi-Agent Reinforcement Learning-based Spectrum Management","display_name":"Backdoor Attacks on Multi-Agent Reinforcement Learning-based Spectrum Management","publication_year":2023,"publication_date":"2023-12-04","ids":{"openalex":"https://openalex.org/W4392175341","doi":"https://doi.org/10.1109/globecom54140.2023.10437779"},"language":"en","primary_location":{"id":"doi:10.1109/globecom54140.2023.10437779","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom54140.2023.10437779","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2023 - 2023 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/A5100660001","display_name":"Hongyi Zhang","orcid":"https://orcid.org/0009-0006-6676-9543"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongyi Zhang","raw_affiliation_strings":["Xidian University,State Key Laboratory of Integrated Service Networks,Shanxi,Xi'an,China,710071"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xidian University,State Key Laboratory of Integrated Service Networks,Shanxi,Xi'an,China,710071","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060002668","display_name":"Mingqian Liu","orcid":"https://orcid.org/0000-0001-9872-9710"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingqian Liu","raw_affiliation_strings":["Xidian University,State Key Laboratory of Integrated Service Networks,Shanxi,Xi'an,China,710071"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xidian University,State Key Laboratory of Integrated Service Networks,Shanxi,Xi'an,China,710071","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102013387","display_name":"Yunfei Chen","orcid":"https://orcid.org/0000-0001-8083-1805"},"institutions":[{"id":"https://openalex.org/I190082696","display_name":"Durham University","ror":"https://ror.org/01v29qb04","country_code":"GB","type":"education","lineage":["https://openalex.org/I190082696"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yunfei Chen","raw_affiliation_strings":["University of Durham,Department of Engineering,Durham,UK,DH1 3LE"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Durham,Department of Engineering,Durham,UK,DH1 3LE","institution_ids":["https://openalex.org/I190082696"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.4513,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.8296866,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"3361","last_page":"3365"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10579","display_name":"Cognitive Radio Networks and Spectrum Sensing","score":0.9955999851226807,"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"}},"topics":[{"id":"https://openalex.org/T10579","display_name":"Cognitive Radio Networks and Spectrum Sensing","score":0.9955999851226807,"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"}},{"id":"https://openalex.org/T10917","display_name":"Smart Grid Security and Resilience","score":0.9915000200271606,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9797999858856201,"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/backdoor","display_name":"Backdoor","score":0.9553391933441162},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.7712100744247437},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6660264730453491},{"id":"https://openalex.org/keywords/reinforcement","display_name":"Reinforcement","score":0.4849677085876465},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.44898703694343567},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3946077823638916},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1580740511417389},{"id":"https://openalex.org/keywords/structural-engineering","display_name":"Structural engineering","score":0.0833219587802887}],"concepts":[{"id":"https://openalex.org/C2781045450","wikidata":"https://www.wikidata.org/wiki/Q254569","display_name":"Backdoor","level":2,"score":0.9553391933441162},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7712100744247437},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6660264730453491},{"id":"https://openalex.org/C67203356","wikidata":"https://www.wikidata.org/wiki/Q1321905","display_name":"Reinforcement","level":2,"score":0.4849677085876465},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.44898703694343567},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3946077823638916},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1580740511417389},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0833219587802887}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/globecom54140.2023.10437779","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom54140.2023.10437779","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2023 - 2023 IEEE Global Communications Conference","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W3034126795","https://openalex.org/W3083185154","https://openalex.org/W3092005433","https://openalex.org/W3180545700","https://openalex.org/W3213485672","https://openalex.org/W4214854086","https://openalex.org/W4296437512","https://openalex.org/W4315630327","https://openalex.org/W4315630375","https://openalex.org/W4317928019","https://openalex.org/W4327928761"],"related_works":["https://openalex.org/W4320031223","https://openalex.org/W4200629851","https://openalex.org/W4281902577","https://openalex.org/W4309417370","https://openalex.org/W4292107232","https://openalex.org/W3009072493","https://openalex.org/W4386080799","https://openalex.org/W3140988292","https://openalex.org/W4317672133","https://openalex.org/W4401407399"],"abstract_inverted_index":{"Effective":[0],"spectrum":[1,60,104,133],"management":[2,61,105,134],"control":[3],"through":[4],"multi-agent":[5,27,64],"deep":[6,28,65,145],"reinforcement":[7,29,66],"learning":[8,30],"holds":[9],"promising":[10],"potential":[11],"for":[12,54,71],"advancing":[13],"wireless":[14],"communication":[15,120],"systems.":[16,147],"However,":[17,110],"backdoor":[18,58,78,113,142],"attacks":[19,143],"can":[20],"compromise":[21],"the":[22,43,72,77,93,100,108,112,127,139],"integrity":[23],"and":[24,38,85,131],"security":[25],"of":[26,95,129,141],"models,":[31],"allowing":[32],"attackers":[33],"to":[34,42,102,126],"manipulate":[35],"their":[36],"behaviour":[37],"cause":[39],"significant":[40],"damage":[41],"system.":[44],"In":[45],"this":[46,96,123],"paper,":[47],"we":[48],"have":[49],"defined":[50],"a":[51,56],"four-step":[52],"process":[53],"designing":[55],"general":[57],"in":[59,118],"based":[62],"on":[63,144],"learning,":[67],"which":[68,98],"involves":[69],"searching":[70],"most":[73],"observed":[74],"channels,":[75,84],"determining":[76],"power":[79],"limit,":[80],"selecting":[81],"feasible":[82],"poisoned":[83],"setting":[86],"up":[87],"induced":[88],"rewards.":[89],"Experimental":[90],"results":[91,117],"demonstrate":[92],"effectiveness":[94],"attack,":[97],"allows":[99],"system":[101],"perform":[103],"without":[106],"triggering":[107],"backdoor.":[109],"when":[111],"is":[114],"triggered,":[115],"it":[116],"severe":[119],"interruptions.":[121],"Overall,":[122],"paper":[124],"contributes":[125],"field":[128],"secure":[130],"reliable":[132],"by":[135],"providing":[136],"insights":[137],"into":[138],"impact":[140],"learning-based":[146]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
