{"id":"https://openalex.org/W4415821400","doi":"https://doi.org/10.1109/tifs.2025.3628121","title":"Reinforcement Learning-Based Efficient Multi-Exit Neural Networks Against Side-Channel Attacks","display_name":"Reinforcement Learning-Based Efficient Multi-Exit Neural Networks Against Side-Channel Attacks","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4415821400","doi":"https://doi.org/10.1109/tifs.2025.3628121"},"language":null,"primary_location":{"id":"doi:10.1109/tifs.2025.3628121","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2025.3628121","pdf_url":null,"source":{"id":"https://openalex.org/S61310614","display_name":"IEEE Transactions on Information Forensics and Security","issn_l":"1556-6013","issn":["1556-6013","1556-6021"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Information Forensics and Security","raw_type":"journal-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/A5091024726","display_name":"Xiaozhen Lu","orcid":"https://orcid.org/0000-0001-8247-0353"},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaozhen Lu","raw_affiliation_strings":["College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0001-8247-0353","affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China","institution_ids":["https://openalex.org/I9842412"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zihan Liu","orcid":"https://orcid.org/0009-0002-2655-8435"},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zihan Liu","raw_affiliation_strings":["College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China"],"raw_orcid":"https://orcid.org/0009-0002-2655-8435","affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China","institution_ids":["https://openalex.org/I9842412"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103140263","display_name":"Zhibo Liu","orcid":"https://orcid.org/0009-0007-4737-9643"},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhibo Liu","raw_affiliation_strings":["College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China"],"raw_orcid":"https://orcid.org/0009-0007-4737-9643","affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China","institution_ids":["https://openalex.org/I9842412"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077407278","display_name":"Yanling Bu","orcid":"https://orcid.org/0000-0001-8207-1125"},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanling Bu","raw_affiliation_strings":["College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0001-8207-1125","affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China","institution_ids":["https://openalex.org/I9842412"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027155270","display_name":"Huaiyu Dai","orcid":"https://orcid.org/0000-0002-0078-4891"},"institutions":[{"id":"https://openalex.org/I137902535","display_name":"North Carolina State University","ror":"https://ror.org/04tj63d06","country_code":"US","type":"education","lineage":["https://openalex.org/I137902535"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Huaiyu Dai","raw_affiliation_strings":["Department of Electrical and Computer Engineering, North Carolina State University, Raleigh, NC, USA"],"raw_orcid":"https://orcid.org/0000-0002-0078-4891","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, North Carolina State University, Raleigh, NC, USA","institution_ids":["https://openalex.org/I137902535"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.16097461,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"20","issue":null,"first_page":"11830","last_page":"11843"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.5174000263214111,"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":0.5174000263214111,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.0681999996304512,"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/T12131","display_name":"Wireless Signal Modulation Classification","score":0.04270000010728836,"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/robustness","display_name":"Robustness (evolution)","score":0.6747999787330627},{"id":"https://openalex.org/keywords/regret","display_name":"Regret","score":0.6482999920845032},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6219000220298767},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.5985999703407288},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.48429998755455017},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.4449999928474426},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.39579999446868896}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.891700029373169},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6747999787330627},{"id":"https://openalex.org/C50817715","wikidata":"https://www.wikidata.org/wiki/Q79895177","display_name":"Regret","level":2,"score":0.6482999920845032},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6219000220298767},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.5985999703407288},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5026000142097473},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.48429998755455017},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.4449999928474426},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.39579999446868896},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.382999986410141},{"id":"https://openalex.org/C761482","wikidata":"https://www.wikidata.org/wiki/Q118093","display_name":"Transmission (telecommunications)","level":2,"score":0.3528999984264374},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.30959999561309814},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.30809998512268066},{"id":"https://openalex.org/C65856478","wikidata":"https://www.wikidata.org/wiki/Q3991682","display_name":"Attack model","level":2,"score":0.30000001192092896},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.28839999437332153},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.2757999897003174},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.27070000767707825},{"id":"https://openalex.org/C203274722","wikidata":"https://www.wikidata.org/wiki/Q7001161","display_name":"Network performance","level":2,"score":0.26429998874664307},{"id":"https://openalex.org/C557945733","wikidata":"https://www.wikidata.org/wiki/Q389772","display_name":"Data transmission","level":2,"score":0.26030001044273376},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2581999897956848}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tifs.2025.3628121","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2025.3628121","pdf_url":null,"source":{"id":"https://openalex.org/S61310614","display_name":"IEEE Transactions on Information Forensics and Security","issn_l":"1556-6013","issn":["1556-6013","1556-6021"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Information Forensics and Security","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1582469052","display_name":null,"funder_award_id":"62402217","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2530942148","display_name":null,"funder_award_id":"ECCS-2203214","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G331018939","display_name":null,"funder_award_id":"U22B2062","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8315569708","display_name":null,"funder_award_id":"62202222","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W2145339207","https://openalex.org/W2611484353","https://openalex.org/W2950802544","https://openalex.org/W2980856918","https://openalex.org/W3049640275","https://openalex.org/W3083321694","https://openalex.org/W3124725679","https://openalex.org/W3164146938","https://openalex.org/W3164261842","https://openalex.org/W3176411177","https://openalex.org/W4210882709","https://openalex.org/W4225683503","https://openalex.org/W4285257856","https://openalex.org/W4292971553","https://openalex.org/W4385819823","https://openalex.org/W4386699405","https://openalex.org/W4386951843","https://openalex.org/W4387011276","https://openalex.org/W4387872678","https://openalex.org/W4388858309","https://openalex.org/W4390190323","https://openalex.org/W4391164477","https://openalex.org/W4393160649","https://openalex.org/W4401070880","https://openalex.org/W4403052684","https://openalex.org/W4404036748","https://openalex.org/W4411203665","https://openalex.org/W4414065104"],"related_works":[],"abstract_inverted_index":{"Distributed":[0],"multi-exit":[1],"neural":[2],"networks":[3],"(MeNNs)":[4],"enable":[5],"mobile":[6],"devices":[7],"to":[8,29,52,81,103,106,111,120],"handle":[9],"complex":[10],"tasks":[11],"such":[12],"as":[13,202],"image":[14],"classification,":[15],"but":[16],"their":[17],"performance":[18],"is":[19,26],"highly":[20],"dependent":[21],"on":[22,48,71,116,173],"transmission":[23],"quality":[24],"and":[25,41,75,100,119,161,182,195,208],"therefore":[27],"vulnerable":[28],"side-channel":[30,38,62,200],"attacks.":[31],"In":[32],"this":[33],"paper,":[34],"we":[35,58,91],"design":[36,59],"a":[37,93,98,112,129,156,168],"attack":[39,63],"model":[40],"propose":[42,128],"an":[43,60],"efficient":[44],"inference":[45,144,190],"framework":[46,154],"based":[47],"the":[49,54,67,72,83,117,122,164],"distributed":[50],"MeNN":[51],"resist":[53],"designed":[55],"attack.":[56],"First,":[57],"intelligent":[61],"model,":[64],"in":[65],"which":[66],"attacker":[68],"can":[69],"eavesdrop":[70],"communication":[73],"channel":[74],"use":[76],"deep":[77],"reinforcement":[78],"learning":[79],"(RL)":[80],"predict":[82],"early":[84,114],"exit":[85,115],"decision":[86],"of":[87],"each":[88],"sample.":[89],"Next,":[90],"develop":[92],"defense":[94],"method":[95,188],"that":[96,133,141,152,186],"employs":[97],"hierarchical":[99],"multi-agent":[101],"RL":[102],"determine":[104],"whether":[105],"infer":[107],"locally":[108],"or":[109,146],"offload":[110],"chosen":[113],"server,":[118],"adjust":[121],"transmit":[123],"power":[124],"accordingly.":[125],"We":[126,150],"further":[127],"critic-guided":[130],"safety":[131],"mechanism":[132],"steers":[134],"local":[135],"agents":[136],"away":[137],"from":[138],"risky":[139],"policies":[140],"would":[142],"cause":[143],"failures":[145],"severe":[147],"data":[148],"leakage.":[149],"prove":[151],"our":[153,187],"enforces":[155],"strict":[157],"instantaneous":[158],"security":[159],"constraint":[160],"asymptotically":[162],"achieves":[163],"optimum":[165],"by":[166],"deriving":[167],"regret":[169],"bound.":[170],"Extensive":[171],"experiments":[172],"several":[174],"datasets":[175],"(including":[176],"CIFAR\u201110,":[177],"CIFAR\u2011100,":[178],"STL\u201110,":[179],"EMNIST,":[180],"FMNIST,":[181],"Stanford":[183],"Cars)":[184],"show":[185],"reduces":[189],"latency,":[191],"improves":[192],"classification":[193],"accuracy,":[194],"significantly":[196],"enhances":[197],"robustness":[198],"against":[199],"attacks,":[201],"compared":[203],"with":[204],"two":[205],"benchmarks":[206],"SCAN":[207],"PCE.":[209]},"counts_by_year":[],"updated_date":"2025-11-11T23:18:09.558992","created_date":"2025-11-03T00:00:00"}
