{"id":"https://openalex.org/W4206805025","doi":"https://doi.org/10.1109/tsmc.2021.3131662","title":"A Hybrid Physics-Based Data-Driven Framework for Anomaly Detection in Industrial Control Systems","display_name":"A Hybrid Physics-Based Data-Driven Framework for Anomaly Detection in Industrial Control Systems","publication_year":2021,"publication_date":"2021-12-13","ids":{"openalex":"https://openalex.org/W4206805025","doi":"https://doi.org/10.1109/tsmc.2021.3131662"},"language":"en","primary_location":{"id":"doi:10.1109/tsmc.2021.3131662","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsmc.2021.3131662","pdf_url":null,"source":{"id":"https://openalex.org/S4210209078","display_name":"IEEE Transactions on Systems Man and Cybernetics Systems","issn_l":"2168-2216","issn":["2168-2216","2168-2232"],"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 Systems, Man, and Cybernetics: Systems","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/A5019304605","display_name":"M. R. Gauthama Raman","orcid":null},"institutions":[{"id":"https://openalex.org/I152815399","display_name":"Singapore University of Technology and Design","ror":"https://ror.org/05j6fvn87","country_code":"SG","type":"education","lineage":["https://openalex.org/I152815399"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"M. R. Gauthama Raman","raw_affiliation_strings":["iTrust, Centre for Cyber Security Research, Singapore University of Technology and Design, Singapore"],"raw_orcid":"https://orcid.org/0000-0002-5285-9330","affiliations":[{"raw_affiliation_string":"iTrust, Centre for Cyber Security Research, Singapore University of Technology and Design, Singapore","institution_ids":["https://openalex.org/I152815399"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041431658","display_name":"Aditya P. Mathur","orcid":"https://orcid.org/0000-0002-9356-6286"},"institutions":[{"id":"https://openalex.org/I152815399","display_name":"Singapore University of Technology and Design","ror":"https://ror.org/05j6fvn87","country_code":"SG","type":"education","lineage":["https://openalex.org/I152815399"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Aditya P. Mathur","raw_affiliation_strings":["iTrust, Centre for Cyber Security Research, Singapore University of Technology and Design, Singapore"],"raw_orcid":"https://orcid.org/0000-0002-9356-6286","affiliations":[{"raw_affiliation_string":"iTrust, Centre for Cyber Security Research, Singapore University of Technology and Design, Singapore","institution_ids":["https://openalex.org/I152815399"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.0785,"has_fulltext":false,"cited_by_count":41,"citation_normalized_percentile":{"value":0.92944858,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"52","issue":"9","first_page":"6003","last_page":"6014"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9995999932289124,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9995999932289124,"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/T10917","display_name":"Smart Grid Security and Resilience","score":0.9993000030517578,"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":0.9955000281333923,"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/anomaly-detection","display_name":"Anomaly detection","score":0.8855313658714294},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.6613371968269348},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.6240930557250977},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.6084191203117371},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5963971018791199},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5792156457901001},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5458512902259827},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5158328413963318},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.48188143968582153},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45824357867240906},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4559018313884735},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.4096301198005676},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.36105602979660034},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32913142442703247},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.12153762578964233},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.12138599157333374}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.8855313658714294},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.6613371968269348},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.6240930557250977},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.6084191203117371},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5963971018791199},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5792156457901001},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5458512902259827},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5158328413963318},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.48188143968582153},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45824357867240906},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4559018313884735},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.4096301198005676},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.36105602979660034},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32913142442703247},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.12153762578964233},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.12138599157333374},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsmc.2021.3131662","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsmc.2021.3131662","pdf_url":null,"source":{"id":"https://openalex.org/S4210209078","display_name":"IEEE Transactions on Systems Man and Cybernetics Systems","issn_l":"2168-2216","issn":["2168-2216","2168-2232"],"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 Systems, Man, and Cybernetics: Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/6","score":0.8399999737739563,"display_name":"Clean water and sanitation"}],"awards":[{"id":"https://openalex.org/G5405695802","display_name":null,"funder_award_id":"NRF2016NCR-NCR002-023","funder_id":"https://openalex.org/F4320320709","funder_display_name":"National Research Foundation Singapore"},{"id":"https://openalex.org/G8101731145","display_name":null,"funder_award_id":"NRF2018NCR-NSOE005-0001","funder_id":"https://openalex.org/F4320320709","funder_display_name":"National Research Foundation Singapore"}],"funders":[{"id":"https://openalex.org/F4320320709","display_name":"National Research Foundation Singapore","ror":"https://ror.org/03cpyc314"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1967456674","https://openalex.org/W2056451850","https://openalex.org/W2293378006","https://openalex.org/W2512094555","https://openalex.org/W2604517708","https://openalex.org/W2608911009","https://openalex.org/W2753616590","https://openalex.org/W2755148105","https://openalex.org/W2886864251","https://openalex.org/W2886897880","https://openalex.org/W2891273344","https://openalex.org/W2896370767","https://openalex.org/W2896487165","https://openalex.org/W2940888709","https://openalex.org/W2962980859","https://openalex.org/W2985870128","https://openalex.org/W3007808067","https://openalex.org/W3087381347","https://openalex.org/W3092239986","https://openalex.org/W3096918578","https://openalex.org/W4288289328","https://openalex.org/W4293718132","https://openalex.org/W6604424860","https://openalex.org/W6732899423","https://openalex.org/W6744375652","https://openalex.org/W6754157402","https://openalex.org/W6754355446","https://openalex.org/W6765696151"],"related_works":["https://openalex.org/W2806741695","https://openalex.org/W4290647774","https://openalex.org/W3189286258","https://openalex.org/W3207797160","https://openalex.org/W3210364259","https://openalex.org/W2964954556","https://openalex.org/W4300558037","https://openalex.org/W2667207928","https://openalex.org/W2912112202","https://openalex.org/W4377864969"],"abstract_inverted_index":{"A":[0],"method":[1],"referred":[2],"to":[3,8,46],"as":[4],"PbNN":[5,39,98],"is":[6],"proposed":[7,73],"detect":[9],"cyber-physical":[10],"attacks":[11],"through":[12,63],"the":[13,19,23,41,48,52,64,67,100,113],"identification":[14],"of":[15,22,44,66,115],"resulting":[16],"anomalies":[17],"in":[18,79],"process":[20],"dynamics":[21],"underlying":[24],"ICS.":[25],"Unlike":[26],"existing":[27,101],"anomaly":[28,105],"detectors":[29,106],"based":[30],"on":[31],"an":[32,80],"abstract":[33],"knowledge":[34,43],"acquired":[35],"from":[36],"operational":[37,61,81],"data,":[38],"utilizes":[40],"design":[42],"ICS":[45],"learn":[47],"complex":[49],"relationships":[50,56],"among":[51],"correlated":[53],"components.":[54],"Such":[55],"are":[57],"accurately":[58],"modeled":[59],"using":[60,109],"data":[62],"application":[65],"deep":[68],"convolution":[69],"neural":[70],"network.":[71],"The":[72,94],"detector":[74],"was":[75],"implemented":[76],"and":[77,91,112],"evaluated":[78],"secure":[82],"water":[83],"treatment":[84],"plant":[85],"by":[86],"launching":[87],"several":[88],"real-time":[89],"stealthy":[90],"coordinated":[92],"attacks.":[93],"results":[95],"indicate":[96],"that":[97],"outperforms":[99],"state-of-the-art":[102],"machine":[103],"learning":[104],"when":[107],"compared":[108],"detection":[110],"accuracy":[111],"rate":[114],"false":[116],"alarms.":[117]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":15},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":2}],"updated_date":"2026-06-13T07:54:00.901334","created_date":"2025-10-10T00:00:00"}