{"id":"https://openalex.org/W7138328696","doi":"https://doi.org/10.1109/tce.2026.3674866","title":"Safety-Aware Intrusion Response System Based on Safe Reinforcement Learning for Cyber-Physical Systems","display_name":"Safety-Aware Intrusion Response System Based on Safe Reinforcement Learning for Cyber-Physical Systems","publication_year":2026,"publication_date":"2026-03-17","ids":{"openalex":"https://openalex.org/W7138328696","doi":"https://doi.org/10.1109/tce.2026.3674866"},"language":null,"primary_location":{"id":"doi:10.1109/tce.2026.3674866","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tce.2026.3674866","pdf_url":null,"source":{"id":"https://openalex.org/S126824455","display_name":"IEEE Transactions on Consumer Electronics","issn_l":"0098-3063","issn":["0098-3063","1558-4127"],"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 Consumer Electronics","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/A5049835513","display_name":"Lin Chen","orcid":"https://orcid.org/0000-0002-6848-5257"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lin Chen","raw_affiliation_strings":["College of Computer Science, Beijing University of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0004-4928-3790","affiliations":[{"raw_affiliation_string":"College of Computer Science, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062711732","display_name":"Yingxu Lai","orcid":"https://orcid.org/0000-0001-9844-1717"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingxu Lai","raw_affiliation_strings":["College of Computer Science, Beijing University of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-9844-1717","affiliations":[{"raw_affiliation_string":"College of Computer Science, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129684470","display_name":"Peng Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Zhao","raw_affiliation_strings":["College of Computer Science, Beijing University of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-2877-3155","affiliations":[{"raw_affiliation_string":"College of Computer Science, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000128396","display_name":"Baoshan Xie","orcid":"https://orcid.org/0000-0001-9283-0260"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Baoshan Xie","raw_affiliation_strings":["College of Computer Science, Beijing University of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100354631","display_name":"Yang Zhang","orcid":"https://orcid.org/0000-0002-0883-8233"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Zhang","raw_affiliation_strings":["College of Computer Science, Beijing University of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0007-3312-659X","affiliations":[{"raw_affiliation_string":"College of Computer Science, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I37796252"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.28443776,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"72","issue":"2","first_page":"2711","last_page":"2723"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.4442000091075897,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.4442000091075897,"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":0.22419999539852142,"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/T10714","display_name":"Software-Defined Networks and 5G","score":0.03060000017285347,"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/intrusion-detection-system","display_name":"Intrusion detection system","score":0.4124999940395355},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.41200000047683716},{"id":"https://openalex.org/keywords/control-system","display_name":"Control system","score":0.40130001306533813},{"id":"https://openalex.org/keywords/intrusion","display_name":"Intrusion","score":0.31279999017715454},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.2865000069141388},{"id":"https://openalex.org/keywords/process-control","display_name":"Process control","score":0.2759000062942505}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.613099992275238},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.43779999017715454},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.4124999940395355},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.41200000047683716},{"id":"https://openalex.org/C17500928","wikidata":"https://www.wikidata.org/wiki/Q959968","display_name":"Control system","level":2,"score":0.40130001306533813},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.3817000091075897},{"id":"https://openalex.org/C158251709","wikidata":"https://www.wikidata.org/wiki/Q354025","display_name":"Intrusion","level":2,"score":0.31279999017715454},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.2865000069141388},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.2770000100135803},{"id":"https://openalex.org/C155386361","wikidata":"https://www.wikidata.org/wiki/Q1649571","display_name":"Process control","level":3,"score":0.2759000062942505},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.27459999918937683},{"id":"https://openalex.org/C27061796","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion prevention system","level":3,"score":0.2565000057220459},{"id":"https://openalex.org/C761482","wikidata":"https://www.wikidata.org/wiki/Q118093","display_name":"Transmission (telecommunications)","level":2,"score":0.251800000667572},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2502000033855438}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tce.2026.3674866","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tce.2026.3674866","pdf_url":null,"source":{"id":"https://openalex.org/S126824455","display_name":"IEEE Transactions on Consumer Electronics","issn_l":"0098-3063","issn":["0098-3063","1558-4127"],"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 Consumer Electronics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1324068874","display_name":null,"funder_award_id":"L241049","funder_id":"https://openalex.org/F4320334977","funder_display_name":"Beijing Municipal Natural Science Foundation"},{"id":"https://openalex.org/G4224648287","display_name":null,"funder_award_id":"62372017","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320334977","display_name":"Beijing Municipal Natural Science Foundation","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0,13,110],"growing":[1],"interconnectivity":[2],"of":[3,21],"consumer":[4],"Cyber-Physical":[5],"systems":[6],"(CPS)":[7],"has":[8,72],"substantially":[9],"elevated":[10],"cybersecurity":[11],"risks.":[12],"Intrusion":[14],"Response":[15],"System":[16],"(IRS),":[17],"a":[18,55,113,128,143],"crucial":[19],"component":[20],"CPS":[22,86,145],"security,":[23,41],"is":[24],"essential":[25],"for":[26,58],"mitigating":[27],"cyber":[28],"threats.":[29],"Ineffective":[30],"response":[31,135],"strategies":[32,136],"can":[33],"pose":[34],"direct":[35],"threats":[36,52],"to":[37,106,133,161,172],"user":[38],"privacy,":[39],"property":[40],"and":[42,53,139,163,186,192],"physical":[43,64],"safety.":[44],"However,":[45],"current":[46],"research":[47],"mainly":[48],"focuses":[49],"on":[50,99,122],"network":[51],"lacks":[54],"systematic":[56],"method":[57],"assessing":[59],"safety":[60,114,138,157],"risks":[61],"in":[62,75,82,142,183],"the":[63,83,100,156,165],"domain.":[65],"Although":[66],"Safe":[67],"Reinforcement":[68],"Learning":[69],"(Safe":[70],"RL)":[71],"shown":[73],"promise":[74],"addressing":[76],"constrained":[77],"optimization":[78,131],"problems,":[79],"its":[80],"application":[81],"complex,":[84],"multi-layered":[85],"risk":[87,120],"environment":[88],"remains":[89],"largely":[90],"unexplored.":[91],"This":[92],"study":[93],"introduces":[94],"an":[95],"IRS":[96],"framework":[97],"based":[98,121],"Constrained":[101],"Markov":[102],"Decision":[103],"Process":[104],"(CMDP)":[105],"address":[107],"these":[108],"challenges.":[109],"approach":[111],"includes":[112],"cost":[115,158],"function":[116],"that":[117],"continuously":[118],"measures":[119],"sensor":[123],"threshold":[124],"breaches.":[125],"It":[126],"employs":[127],"hierarchical":[129],"policy":[130],"algorithm":[132],"develop":[134],"prioritizing":[137],"effectiveness.":[140],"Experiments":[141],"simulated":[144],"testbed":[146],"demonstrate":[147],"that,":[148],"compared":[149],"with":[150],"existing":[151,180],"IRS-based":[152],"methods,":[153],"SAIRS":[154],"reduces":[155],"from":[159],"5.07":[160],"0":[162],"improves":[164],"defense":[166,187],"success":[167],"rate":[168],"by":[169,190],"7%":[170],"relative":[171],"other":[173],"safe":[174],"RL":[175],"approaches;":[176],"additionally,":[177],"it":[178],"surpasses":[179],"MPC-based":[181],"methods":[182],"computational":[184],"efficiency":[185,189],"clearing":[188],"39.23":[191],"1.45":[193],"times,":[194],"respectively.":[195]},"counts_by_year":[],"updated_date":"2026-06-09T06:18:44.609144","created_date":"2026-03-18T00:00:00"}