{"id":"https://openalex.org/W3193745882","doi":"https://doi.org/10.1109/ssp49050.2021.9513837","title":"Quickest Detection of Stochastic False Data Injection Attacks with Unknown Parameters","display_name":"Quickest Detection of Stochastic False Data Injection Attacks with Unknown Parameters","publication_year":2021,"publication_date":"2021-07-11","ids":{"openalex":"https://openalex.org/W3193745882","doi":"https://doi.org/10.1109/ssp49050.2021.9513837","mag":"3193745882"},"language":"en","primary_location":{"id":"doi:10.1109/ssp49050.2021.9513837","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssp49050.2021.9513837","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Statistical Signal Processing Workshop (SSP)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://hdl.handle.net/11250/2988119","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5088195046","display_name":"Bettina D. Barros","orcid":null},"institutions":[{"id":"https://openalex.org/I4210165875","display_name":"NTNU Samfunnsforskning","ror":"https://ror.org/05pv30e80","country_code":"NO","type":"facility","lineage":["https://openalex.org/I4210165875"]}],"countries":["NO"],"is_corresponding":true,"raw_author_name":"Bettina D. Barros","raw_affiliation_strings":["NTNU, Trondheim, Norway"],"affiliations":[{"raw_affiliation_string":"NTNU, Trondheim, Norway","institution_ids":["https://openalex.org/I4210165875"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031758842","display_name":"Naveen K. D. Venkategowda","orcid":"https://orcid.org/0000-0001-8145-7392"},"institutions":[{"id":"https://openalex.org/I4210165875","display_name":"NTNU Samfunnsforskning","ror":"https://ror.org/05pv30e80","country_code":"NO","type":"facility","lineage":["https://openalex.org/I4210165875"]},{"id":"https://openalex.org/I102134673","display_name":"Link\u00f6ping University","ror":"https://ror.org/05ynxx418","country_code":"SE","type":"education","lineage":["https://openalex.org/I102134673"]}],"countries":["NO","SE"],"is_corresponding":false,"raw_author_name":"Naveen K. D. Venkategowda","raw_affiliation_strings":["Link\u00f6ping University, Sweden","NTNU, Trondheim, Norway"],"affiliations":[{"raw_affiliation_string":"Link\u00f6ping University, Sweden","institution_ids":["https://openalex.org/I102134673"]},{"raw_affiliation_string":"NTNU, Trondheim, Norway","institution_ids":["https://openalex.org/I4210165875"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059938646","display_name":"Stefan Werner","orcid":"https://orcid.org/0000-0003-0148-4724"},"institutions":[{"id":"https://openalex.org/I4210165875","display_name":"NTNU Samfunnsforskning","ror":"https://ror.org/05pv30e80","country_code":"NO","type":"facility","lineage":["https://openalex.org/I4210165875"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"Stefan Werner","raw_affiliation_strings":["NTNU, Trondheim, Norway"],"affiliations":[{"raw_affiliation_string":"NTNU, Trondheim, Norway","institution_ids":["https://openalex.org/I4210165875"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5088195046"],"corresponding_institution_ids":["https://openalex.org/I4210165875"],"apc_list":null,"apc_paid":null,"fwci":0.1721,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.67220111,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"426","last_page":"430"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11443","display_name":"Advanced Statistical Process Monitoring","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11443","display_name":"Advanced Statistical Process Monitoring","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9987000226974487,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9934999942779541,"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/false-alarm","display_name":"False alarm","score":0.7672230005264282},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.7151919007301331},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.7139678597450256},{"id":"https://openalex.org/keywords/constant-false-alarm-rate","display_name":"Constant false alarm rate","score":0.6706860065460205},{"id":"https://openalex.org/keywords/likelihood-ratio-test","display_name":"Likelihood-ratio test","score":0.6254363059997559},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5426320433616638},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.5241337418556213},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5122260451316833},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.48939743638038635},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.45941290259361267},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.4225746989250183},{"id":"https://openalex.org/keywords/multivariate-normal-distribution","display_name":"Multivariate normal distribution","score":0.41899800300598145},{"id":"https://openalex.org/keywords/statistical-hypothesis-testing","display_name":"Statistical hypothesis testing","score":0.4142424464225769},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4131605625152588},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.3345728814601898},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.07553526759147644}],"concepts":[{"id":"https://openalex.org/C2776836416","wikidata":"https://www.wikidata.org/wiki/Q1364844","display_name":"False alarm","level":2,"score":0.7672230005264282},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.7151919007301331},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.7139678597450256},{"id":"https://openalex.org/C77052588","wikidata":"https://www.wikidata.org/wiki/Q644307","display_name":"Constant false alarm rate","level":2,"score":0.6706860065460205},{"id":"https://openalex.org/C9483764","wikidata":"https://www.wikidata.org/wiki/Q585740","display_name":"Likelihood-ratio test","level":2,"score":0.6254363059997559},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5426320433616638},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.5241337418556213},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5122260451316833},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.48939743638038635},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.45941290259361267},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4225746989250183},{"id":"https://openalex.org/C177384507","wikidata":"https://www.wikidata.org/wiki/Q1149000","display_name":"Multivariate normal distribution","level":3,"score":0.41899800300598145},{"id":"https://openalex.org/C87007009","wikidata":"https://www.wikidata.org/wiki/Q210832","display_name":"Statistical hypothesis testing","level":2,"score":0.4142424464225769},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4131605625152588},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.3345728814601898},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.07553526759147644},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ssp49050.2021.9513837","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssp49050.2021.9513837","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Statistical Signal Processing Workshop (SSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:ntnuopen.ntnu.no:11250/2988119","is_oa":true,"landing_page_url":"https://hdl.handle.net/11250/2988119","pdf_url":null,"source":{"id":"https://openalex.org/S4306401716","display_name":"Duo Research Archive (University of Oslo)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I184942183","host_organization_name":"University of Oslo","host_organization_lineage":["https://openalex.org/I184942183"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/bookPart"}],"best_oa_location":{"id":"pmh:oai:ntnuopen.ntnu.no:11250/2988119","is_oa":true,"landing_page_url":"https://hdl.handle.net/11250/2988119","pdf_url":null,"source":{"id":"https://openalex.org/S4306401716","display_name":"Duo Research Archive (University of Oslo)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I184942183","host_organization_name":"University of Oslo","host_organization_lineage":["https://openalex.org/I184942183"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/bookPart"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W100923692","https://openalex.org/W1533983758","https://openalex.org/W1967665616","https://openalex.org/W2018319586","https://openalex.org/W2019841176","https://openalex.org/W2022229650","https://openalex.org/W2071992589","https://openalex.org/W2089561958","https://openalex.org/W2092224475","https://openalex.org/W2105773843","https://openalex.org/W2122406212","https://openalex.org/W2140456136","https://openalex.org/W2530103553","https://openalex.org/W2733510830","https://openalex.org/W2780545917","https://openalex.org/W2783683139","https://openalex.org/W2890942945","https://openalex.org/W2904588591","https://openalex.org/W2948566387","https://openalex.org/W2951694401","https://openalex.org/W2963766209","https://openalex.org/W3105735656","https://openalex.org/W3120306033","https://openalex.org/W4233511778","https://openalex.org/W6675810980","https://openalex.org/W6678455948"],"related_works":["https://openalex.org/W1983393909","https://openalex.org/W2167992111","https://openalex.org/W2030759397","https://openalex.org/W2762654808","https://openalex.org/W2150496749","https://openalex.org/W2097772921","https://openalex.org/W2170481245","https://openalex.org/W2080824149","https://openalex.org/W2354373235","https://openalex.org/W2058750705"],"abstract_inverted_index":{"This":[0],"paper":[1],"considers":[2],"a":[3,22,84,96],"multivariate":[4],"quickest":[5,69],"detection":[6,115],"problem":[7],"with":[8,72],"false":[9,90],"data":[10],"injection":[11],"(FDI)":[12],"attacks":[13],"in":[14,55],"internet":[15],"of":[16,61,79,117],"things":[17],"(IoT)":[18],"systems.":[19],"We":[20,110],"derive":[21],"sequential":[23,136],"generalized":[24],"likelihood":[25],"ratio":[26],"test":[27],"(GLRT)":[28],"for":[29,121],"zero-mean":[30],"Gaussian":[31],"FDI":[32],"attacks.":[33],"Exploiting":[34],"the":[35,56,62,89,101,113,118,130,134],"fact":[36],"that":[37,129],"covariance":[38,57],"matrices":[39],"are":[40,105],"positive,":[41],"we":[42,82,94],"propose":[43],"strategies":[44],"to":[45,77,87,99,108],"detect":[46],"positive":[47],"semi-definite":[48],"matrix":[49],"additions":[50],"rather":[51],"than":[52],"arbitrary":[53],"changes":[54],"matrix.":[58],"The":[59],"distribution":[60],"GLRT":[63,137],"is":[64],"only":[65],"known":[66],"asymptotically":[67],"whereas":[68],"detectors":[70],"deal":[71],"short":[73],"sequences,":[74,103],"thereby":[75],"leading":[76],"loss":[78],"performance.":[80],"Therefore,":[81],"use":[83],"finite-sample":[85],"correction":[86],"reduce":[88],"alarm":[91],"rate.":[92],"Further,":[93],"provide":[95],"numerical":[97],"approach":[98],"estimate":[100],"threshold":[102,125],"which":[104],"analytically":[106],"intractable":[107],"compute.":[109],"also":[111],"compare":[112],"average":[114],"delay":[116],"proposed":[119,131],"detector":[120,132],"constant":[122],"and":[123],"varying":[124],"sequences.":[126],"Simulations":[127],"showed":[128],"outperforms":[133],"standard":[135],"detector.":[138]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}