{"id":"https://openalex.org/W2982016561","doi":"https://doi.org/10.1109/pimrcw.2019.8880846","title":"Statistical Appliance Inference in the Smart Grid by Machine Learning","display_name":"Statistical Appliance Inference in the Smart Grid by Machine Learning","publication_year":2019,"publication_date":"2019-09-01","ids":{"openalex":"https://openalex.org/W2982016561","doi":"https://doi.org/10.1109/pimrcw.2019.8880846","mag":"2982016561"},"language":"en","primary_location":{"id":"doi:10.1109/pimrcw.2019.8880846","is_oa":false,"landing_page_url":"https://doi.org/10.1109/pimrcw.2019.8880846","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 30th International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC Workshops)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5078037266","display_name":"Zeki Bilgin","orcid":null},"institutions":[{"id":"https://openalex.org/I1306339040","display_name":"Ericsson (Sweden)","ror":"https://ror.org/05a7rhx54","country_code":"SE","type":"company","lineage":["https://openalex.org/I1306339040"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Zeki Bilgin","raw_affiliation_strings":["Ericsson Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ericsson Research","institution_ids":["https://openalex.org/I1306339040"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024757608","display_name":"Emrah Tomur","orcid":"https://orcid.org/0000-0001-8985-4974"},"institutions":[{"id":"https://openalex.org/I1306339040","display_name":"Ericsson (Sweden)","ror":"https://ror.org/05a7rhx54","country_code":"SE","type":"company","lineage":["https://openalex.org/I1306339040"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Emrah Tomur","raw_affiliation_strings":["Ericsson Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ericsson Research","institution_ids":["https://openalex.org/I1306339040"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001715684","display_name":"Mehmet Ersoy","orcid":"https://orcid.org/0000-0002-0724-2825"},"institutions":[{"id":"https://openalex.org/I1306339040","display_name":"Ericsson (Sweden)","ror":"https://ror.org/05a7rhx54","country_code":"SE","type":"company","lineage":["https://openalex.org/I1306339040"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Mehmet Akif Ersoy","raw_affiliation_strings":["Ericsson Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ericsson Research","institution_ids":["https://openalex.org/I1306339040"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048028150","display_name":"Elif \u00dcst\u00fcnda\u011f Soykan","orcid":"https://orcid.org/0000-0002-7908-1469"},"institutions":[{"id":"https://openalex.org/I1306339040","display_name":"Ericsson (Sweden)","ror":"https://ror.org/05a7rhx54","country_code":"SE","type":"company","lineage":["https://openalex.org/I1306339040"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Elif Ustundag Soykan","raw_affiliation_strings":["Ericsson Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ericsson Research","institution_ids":["https://openalex.org/I1306339040"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I1306339040"],"apc_list":null,"apc_paid":null,"fwci":0.4374,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.67836257,"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":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9987000226974487,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9987000226974487,"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/T10603","display_name":"Smart Grid Energy Management","score":0.9919999837875366,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10917","display_name":"Smart Grid Security and Resilience","score":0.988099992275238,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7977350950241089},{"id":"https://openalex.org/keywords/smart-grid","display_name":"Smart grid","score":0.7208989262580872},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6242271065711975},{"id":"https://openalex.org/keywords/power-consumption","display_name":"Power consumption","score":0.6167453527450562},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6153345704078674},{"id":"https://openalex.org/keywords/consumption","display_name":"Consumption (sociology)","score":0.5498384237289429},{"id":"https://openalex.org/keywords/internet-of-things","display_name":"Internet of Things","score":0.5340555906295776},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.517073929309845},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.5167036056518555},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.4751196503639221},{"id":"https://openalex.org/keywords/work","display_name":"Work (physics)","score":0.437456876039505},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.43342962861061096},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41152191162109375},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.4062715768814087},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3666074573993683},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.34776249527931213},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.29653728008270264},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.29298868775367737},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09712633490562439}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7977350950241089},{"id":"https://openalex.org/C10558101","wikidata":"https://www.wikidata.org/wiki/Q689855","display_name":"Smart grid","level":2,"score":0.7208989262580872},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6242271065711975},{"id":"https://openalex.org/C2984118289","wikidata":"https://www.wikidata.org/wiki/Q29954","display_name":"Power consumption","level":3,"score":0.6167453527450562},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6153345704078674},{"id":"https://openalex.org/C30772137","wikidata":"https://www.wikidata.org/wiki/Q5164762","display_name":"Consumption (sociology)","level":2,"score":0.5498384237289429},{"id":"https://openalex.org/C81860439","wikidata":"https://www.wikidata.org/wiki/Q251212","display_name":"Internet of Things","level":2,"score":0.5340555906295776},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.517073929309845},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.5167036056518555},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.4751196503639221},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.437456876039505},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.43342962861061096},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41152191162109375},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.4062715768814087},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3666074573993683},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.34776249527931213},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.29653728008270264},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.29298868775367737},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09712633490562439},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"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/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"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/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/pimrcw.2019.8880846","is_oa":false,"landing_page_url":"https://doi.org/10.1109/pimrcw.2019.8880846","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 30th International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC Workshops)","raw_type":"proceedings-article"},{"id":"pmh:oai:ueaeprints.uea.ac.uk:87432","is_oa":false,"landing_page_url":"https://ueaeprints.uea.ac.uk/id/eprint/87432/","pdf_url":null,"source":{"id":"https://openalex.org/S4306400384","display_name":"UEA Digital Repository (University of East Anglia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1118541","host_organization_name":"University of East Anglia","host_organization_lineage":["https://openalex.org/I1118541"],"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":"Book Section"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.6800000071525574,"display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1975153313","https://openalex.org/W1993673439","https://openalex.org/W2018275882","https://openalex.org/W2069872789","https://openalex.org/W2071637194","https://openalex.org/W2101234009","https://openalex.org/W2123910460","https://openalex.org/W2159065056","https://openalex.org/W2292956891","https://openalex.org/W2440876130","https://openalex.org/W2471129008","https://openalex.org/W2473418344","https://openalex.org/W2528618933","https://openalex.org/W2552744522","https://openalex.org/W2621932216","https://openalex.org/W2730936454","https://openalex.org/W2791622075","https://openalex.org/W2963560312","https://openalex.org/W6675354045"],"related_works":["https://openalex.org/W4390608645","https://openalex.org/W4247566972","https://openalex.org/W2960264696","https://openalex.org/W3090563135","https://openalex.org/W2497432351","https://openalex.org/W4206777497","https://openalex.org/W2910064364","https://openalex.org/W4255224757","https://openalex.org/W2898021358","https://openalex.org/W2354255779"],"abstract_inverted_index":{"Smart":[0],"Grid":[1],"has":[2],"been":[3],"attracting":[4],"more":[5],"interest":[6],"than":[7],"ever":[8],"thanks":[9],"to":[10,111],"emergence":[11],"of":[12,32,48,99,128],"enabling":[13],"technologies":[14],"such":[15],"as":[16],"5G":[17],"and":[18,30,119],"IoT.":[19],"Yet,":[20],"there":[21],"are":[22],"some":[23],"long-standing":[24],"privacy":[25],"concerns":[26],"about":[27],"revealing":[28],"habits":[29],"lifestyles":[31],"people":[33],"from":[34,73],"fine-grained":[35,59],"power":[36,60],"consumption":[37,61,74,97],"data":[38,62,75,98,130],"collected":[39],"through":[40],"smart":[41],"meters.":[42],"In":[43,136],"this":[44,49,113,149],"context,":[45],"the":[46,132,145],"contribution":[47],"work":[50],"is":[51],"twofold:":[52],"First,":[53],"we":[54,82,138],"empirically":[55],"demonstrate":[56],"how":[57,104],"appliance-level":[58],"can":[63,88,107],"reveal":[64],"households'":[65],"routines":[66],"simply":[67],"using":[68,95],"probability":[69],"density":[70],"estimations":[71],"derived":[72],"without":[76],"requiring":[77],"any":[78],"complex":[79],"analysis.":[80],"Second,":[81],"point":[83],"out":[84],"that":[85],"appliance":[86],"types":[87],"be":[89,108],"identified":[90],"in":[91,115,148],"a":[92],"targeted":[93],"house":[94],"circuit-level":[96],"other":[100],"houses.":[101],"We":[102],"show":[103],"machine":[105],"learning":[106],"used":[109],"maliciously":[110],"realize":[112],"threat":[114],"an":[116],"automatic":[117],"manner":[118],"achieve":[120],"high":[121],"success":[122],"rate":[123],"even":[124],"with":[125],"limited":[126],"amount":[127],"training":[129],"on":[131,141],"public":[133],"REDD":[134],"dataset.":[135],"addition,":[137],"provide":[139],"discussions":[140],"possible":[142],"countermeasures":[143],"against":[144],"threats":[146],"examined":[147],"study.":[150]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}