{"id":"https://openalex.org/W3181784683","doi":"https://doi.org/10.1109/icps49255.2021.9468197","title":"Optimal Linear FDI Attacks with Side Information: A Comparative Study","display_name":"Optimal Linear FDI Attacks with Side Information: A Comparative Study","publication_year":2021,"publication_date":"2021-05-10","ids":{"openalex":"https://openalex.org/W3181784683","doi":"https://doi.org/10.1109/icps49255.2021.9468197","mag":"3181784683"},"language":"en","primary_location":{"id":"doi:10.1109/icps49255.2021.9468197","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icps49255.2021.9468197","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 4th IEEE International Conference on Industrial Cyber-Physical Systems (ICPS)","raw_type":"proceedings-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/A5001092290","display_name":"Jing Zhou","orcid":"https://orcid.org/0000-0003-1676-5991"},"institutions":[{"id":"https://openalex.org/I154425047","display_name":"University of Alberta","ror":"https://ror.org/0160cpw27","country_code":"CA","type":"education","lineage":["https://openalex.org/I154425047"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Jing Zhou","raw_affiliation_strings":["University of Alberta, Edmonton, CA"],"affiliations":[{"raw_affiliation_string":"University of Alberta, Edmonton, CA","institution_ids":["https://openalex.org/I154425047"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080674902","display_name":"Jun Shang","orcid":"https://orcid.org/0000-0003-0624-3655"},"institutions":[{"id":"https://openalex.org/I154425047","display_name":"University of Alberta","ror":"https://ror.org/0160cpw27","country_code":"CA","type":"education","lineage":["https://openalex.org/I154425047"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Jun Shang","raw_affiliation_strings":["University of Alberta, Edmonton, CA"],"affiliations":[{"raw_affiliation_string":"University of Alberta, Edmonton, CA","institution_ids":["https://openalex.org/I154425047"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037989105","display_name":"Tongwen Chen","orcid":"https://orcid.org/0000-0002-1699-7947"},"institutions":[{"id":"https://openalex.org/I154425047","display_name":"University of Alberta","ror":"https://ror.org/0160cpw27","country_code":"CA","type":"education","lineage":["https://openalex.org/I154425047"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Tongwen Chen","raw_affiliation_strings":["University of Alberta, Edmonton, CA"],"affiliations":[{"raw_affiliation_string":"University of Alberta, Edmonton, CA","institution_ids":["https://openalex.org/I154425047"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5001092290"],"corresponding_institution_ids":["https://openalex.org/I154425047"],"apc_list":null,"apc_paid":null,"fwci":1.236,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.78978979,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"138","last_page":"143"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10917","display_name":"Smart Grid Security and Resilience","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T10917","display_name":"Smart Grid Security and Resilience","score":0.9998000264167786,"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":0.9861999750137329,"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/T10270","display_name":"Blockchain Technology Applications and Security","score":0.9678999781608582,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/computer-science","display_name":"Computer science","score":0.6233844757080078},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.5443846583366394},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.47706902027130127},{"id":"https://openalex.org/keywords/convex-optimization","display_name":"Convex optimization","score":0.474163681268692},{"id":"https://openalex.org/keywords/scalar","display_name":"Scalar (mathematics)","score":0.45837002992630005},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.45491504669189453},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.4394012987613678},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.432259738445282},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.42398688197135925},{"id":"https://openalex.org/keywords/regular-polygon","display_name":"Regular polygon","score":0.3124847412109375},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3114326000213623},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.30375924706459045},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.208529531955719},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09142756462097168}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6233844757080078},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.5443846583366394},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.47706902027130127},{"id":"https://openalex.org/C157972887","wikidata":"https://www.wikidata.org/wiki/Q463359","display_name":"Convex optimization","level":3,"score":0.474163681268692},{"id":"https://openalex.org/C57691317","wikidata":"https://www.wikidata.org/wiki/Q1289248","display_name":"Scalar (mathematics)","level":2,"score":0.45837002992630005},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.45491504669189453},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.4394012987613678},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.432259738445282},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.42398688197135925},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.3124847412109375},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3114326000213623},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.30375924706459045},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.208529531955719},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09142756462097168},{"id":"https://openalex.org/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icps49255.2021.9468197","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icps49255.2021.9468197","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 4th IEEE International Conference on Industrial Cyber-Physical Systems (ICPS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6800000071525574,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320322725","display_name":"China Scholarship Council","ror":"https://ror.org/04atp4p48"},{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1993036147","https://openalex.org/W2038651258","https://openalex.org/W2039427951","https://openalex.org/W2041587044","https://openalex.org/W2084549379","https://openalex.org/W2402911760","https://openalex.org/W2568479698","https://openalex.org/W2589039213","https://openalex.org/W2613841561","https://openalex.org/W2627024038","https://openalex.org/W2758737610","https://openalex.org/W2780545917","https://openalex.org/W2784198128","https://openalex.org/W2811475107","https://openalex.org/W2906912256","https://openalex.org/W2961536906","https://openalex.org/W2985525905","https://openalex.org/W3089954048","https://openalex.org/W3138139098","https://openalex.org/W3183805430"],"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/W4300558037","https://openalex.org/W2667207928","https://openalex.org/W2912112202","https://openalex.org/W4377864969","https://openalex.org/W3030345572"],"abstract_inverted_index":{"This":[0],"paper":[1],"studies":[2],"the":[3,16,23,53,68,99,105],"problem":[4],"of":[5,32,58,83],"false":[6],"data":[7],"injection":[8],"attacks":[9,64],"against":[10],"remote":[11,115],"state":[12,116],"estimation.":[13,117],"We":[14],"consider":[15],"scenario":[17],"where":[18],"malicious":[19],"attackers":[20],"can":[21,44,102],"intercept":[22],"original":[24],"innovation":[25],"and":[26,108],"also":[27],"obtain":[28],"some":[29],"side":[30],"information":[31],"system":[33],"states":[34],"with":[35,96],"an":[36],"extra":[37],"sensor.":[38],"A":[39],"linear":[40],"attack":[41,70,84,101],"strategy":[42,71],"that":[43],"successfully":[45,103],"bypass":[46,104],"anomaly":[47,106],"detectors":[48],"is":[49,65,72,89],"proposed":[50,100],"based":[51],"on":[52],"combined":[54],"information.":[55],"The":[56],"recursion":[57],"a":[59,76],"posteriori":[60],"error":[61],"covariance":[62],"under":[63],"derived;":[66],"then":[67],"optimal":[69],"obtained":[73],"by":[74],"solving":[75],"convex":[77],"optimization":[78],"problem.":[79],"An":[80],"explicit":[81],"solution":[82],"coefficients":[85],"for":[86],"scalar":[87],"systems":[88],"derived.":[90],"Simulation":[91],"results":[92],"show":[93],"that,":[94],"compared":[95],"existing":[97],"work,":[98],"detector":[107],"cause":[109],"more":[110],"severe":[111],"performance":[112],"degradation":[113],"in":[114]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}