{"id":"https://openalex.org/W3013678595","doi":"https://doi.org/10.1109/tac.2020.3007383","title":"On the Complexity and Approximability of Optimal Sensor Selection and Attack for Kalman Filtering","display_name":"On the Complexity and Approximability of Optimal Sensor Selection and Attack for Kalman Filtering","publication_year":2020,"publication_date":"2020-07-07","ids":{"openalex":"https://openalex.org/W3013678595","doi":"https://doi.org/10.1109/tac.2020.3007383","mag":"3013678595"},"language":"en","primary_location":{"id":"doi:10.1109/tac.2020.3007383","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tac.2020.3007383","pdf_url":null,"source":{"id":"https://openalex.org/S184954342","display_name":"IEEE Transactions on Automatic Control","issn_l":"0018-9286","issn":["0018-9286","1558-2523","2334-3303"],"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 Automatic Control","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2003.11951","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Lintao Ye","orcid":"https://orcid.org/0000-0001-8608-5815"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lintao Ye","raw_affiliation_strings":["School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA"],"raw_orcid":"https://orcid.org/0000-0001-8608-5815","affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Nathaniel Woodford","orcid":"https://orcid.org/0000-0003-1778-334X"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nathaniel Woodford","raw_affiliation_strings":["School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA"],"raw_orcid":"https://orcid.org/0000-0003-1778-334X","affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Sandip Roy","orcid":"https://orcid.org/0000-0002-5558-9698"},"institutions":[{"id":"https://openalex.org/I72951846","display_name":"Washington State University","ror":"https://ror.org/05dk0ce17","country_code":"US","type":"education","lineage":["https://openalex.org/I72951846"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sandip Roy","raw_affiliation_strings":["School of Electrical Engineering and Computer Science, Washington State University, Pullman, WA, USA"],"raw_orcid":"https://orcid.org/0000-0002-5558-9698","affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Computer Science, Washington State University, Pullman, WA, USA","institution_ids":["https://openalex.org/I72951846"]}]},{"author_position":"last","author":{"id":null,"display_name":"Shreyas Sundaram","orcid":"https://orcid.org/0000-0002-5390-2505"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shreyas Sundaram","raw_affiliation_strings":["School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA"],"raw_orcid":"https://orcid.org/0000-0002-5390-2505","affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.8777,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.86081269,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"66","issue":"5","first_page":"2146","last_page":"2161"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.6100000143051147,"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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.6100000143051147,"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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.09790000319480896,"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/T10249","display_name":"Distributed Control Multi-Agent Systems","score":0.07580000162124634,"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/greedy-algorithm","display_name":"Greedy algorithm","score":0.7303000092506409},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.7055000066757202},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.6758000254631042},{"id":"https://openalex.org/keywords/trace","display_name":"TRACE (psycholinguistics)","score":0.6151000261306763},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.5669999718666077},{"id":"https://openalex.org/keywords/approximation-algorithm","display_name":"Approximation algorithm","score":0.5302000045776367},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.47189998626708984}],"concepts":[{"id":"https://openalex.org/C51823790","wikidata":"https://www.wikidata.org/wiki/Q504353","display_name":"Greedy algorithm","level":2,"score":0.7303000092506409},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.7055000066757202},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.6758000254631042},{"id":"https://openalex.org/C75291252","wikidata":"https://www.wikidata.org/wiki/Q1315756","display_name":"TRACE (psycholinguistics)","level":2,"score":0.6151000261306763},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5888000130653381},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.5669999718666077},{"id":"https://openalex.org/C148764684","wikidata":"https://www.wikidata.org/wiki/Q621751","display_name":"Approximation algorithm","level":2,"score":0.5302000045776367},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5224000215530396},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.47189998626708984},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.44429999589920044},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4431999921798706},{"id":"https://openalex.org/C9810830","wikidata":"https://www.wikidata.org/wiki/Q635384","display_name":"Maximum a posteriori estimation","level":3,"score":0.3422999978065491},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.3294999897480011},{"id":"https://openalex.org/C114275822","wikidata":"https://www.wikidata.org/wiki/Q621512","display_name":"Linear dynamical system","level":3,"score":0.31139999628067017},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2992999851703644},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.29339998960494995},{"id":"https://openalex.org/C150679823","wikidata":"https://www.wikidata.org/wiki/Q5436946","display_name":"Fast Kalman filter","level":4,"score":0.27480000257492065},{"id":"https://openalex.org/C206833254","wikidata":"https://www.wikidata.org/wiki/Q5421817","display_name":"Extended Kalman filter","level":3,"score":0.26159998774528503}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tac.2020.3007383","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tac.2020.3007383","pdf_url":null,"source":{"id":"https://openalex.org/S184954342","display_name":"IEEE Transactions on Automatic Control","issn_l":"0018-9286","issn":["0018-9286","1558-2523","2334-3303"],"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 Automatic Control","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2003.11951","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2003.11951","pdf_url":"https://arxiv.org/pdf/2003.11951","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2003.11951","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2003.11951","pdf_url":"https://arxiv.org/pdf/2003.11951","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1316245627","display_name":null,"funder_award_id":"CMMI-1635014","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4493840357","display_name":null,"funder_award_id":"CMMI-1635184","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W391578156","https://openalex.org/W1501233054","https://openalex.org/W1680189815","https://openalex.org/W1803898544","https://openalex.org/W1829644108","https://openalex.org/W1938602245","https://openalex.org/W1963646571","https://openalex.org/W1980183459","https://openalex.org/W1986085795","https://openalex.org/W2003949298","https://openalex.org/W2015713866","https://openalex.org/W2028781966","https://openalex.org/W2038651258","https://openalex.org/W2044803016","https://openalex.org/W2045333994","https://openalex.org/W2058590322","https://openalex.org/W2098897917","https://openalex.org/W2100729440","https://openalex.org/W2122285088","https://openalex.org/W2132443513","https://openalex.org/W2136032111","https://openalex.org/W2145185087","https://openalex.org/W2159416808","https://openalex.org/W2169207653","https://openalex.org/W2176421236","https://openalex.org/W2288481136","https://openalex.org/W2340384825","https://openalex.org/W2343541124","https://openalex.org/W2404139833","https://openalex.org/W2582646431","https://openalex.org/W2604420937","https://openalex.org/W2912412583","https://openalex.org/W2963334607","https://openalex.org/W2963595662","https://openalex.org/W2964202295","https://openalex.org/W2992934504","https://openalex.org/W6639467292","https://openalex.org/W6679608865"],"related_works":[],"abstract_inverted_index":{"Given":[0],"a":[1,30,33,96,126,143,146],"linear":[2],"dynamical":[3],"system":[4],"affected":[5],"by":[6,81],"stochastic":[7],"noise,":[8],"we":[9,94,155],"consider":[10],"the":[11,25,28,38,49,74,90,108,120,138,141,151],"problem":[12,109,121,167],"of":[13,18,27,37,68,89,110,122,128,140,150],"selecting":[14],"an":[15],"optimal":[16],"set":[17,127],"sensors":[19],"(at":[20],"design":[21],"time)":[22],"to":[23,42,136],"minimize":[24],"trace":[26,139],"steady-state":[29,142],"priori":[31,144],"or":[32,145],"posteriori":[34,147],"error":[35,148],"covariance":[36,149],"Kalman":[39,115,152],"filter,":[40],"subject":[41],"certain":[43],"selection":[44,70,113],"budget":[45,134],"constraints.":[46],"We":[47,117],"show":[48,156,169],"fundamental":[50],"result":[51],"that":[52,100,157,171],"there":[53,158],"is":[54,159],"no":[55,160],"polynomial-time":[56,161],"constant-factor":[57,79,162],"approximation":[58,163],"algorithm":[59,164],"for":[60,107,114,165],"this":[61,166],"problem.":[62],"This":[63],"contrasts":[64],"with":[65],"other":[66],"classes":[67],"sensor":[69,112],"problems":[71],"studied":[72],"in":[73],"literature,":[75],"which":[76],"typically":[77],"pursue":[78],"approximations":[80],"leveraging":[82],"greedy":[83,101,172],"algorithms":[84,102,173],"and":[85,168],"submodularity":[86],"(or":[87],"supermodularity)":[88],"cost":[91],"function.":[92],"Here,":[93],"provide":[95],"specific":[97],"example":[98],"showing":[99],"can":[103,174],"perform":[104,175],"arbitrarily":[105,176],"poorly":[106],"design-time":[111],"filtering.":[116],"then":[118],"study":[119],"attacking":[123],"(i.e.,":[124],"removing)":[125],"installed":[129],"sensors,":[130],"under":[131],"predefined":[132],"attack":[133],"constraints,":[135],"maximize":[137],"filter.":[153],"Again,":[154],"specifically":[170],"poorly.":[177]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4}],"updated_date":"2026-08-05T07:39:15.569665","created_date":"2020-04-03T00:00:00"}
