{"id":"https://openalex.org/W4285813893","doi":"https://doi.org/10.1109/iwcmc55113.2022.9825224","title":"OPTICS-Based Outlier Detection with Newton Classification","display_name":"OPTICS-Based Outlier Detection with Newton Classification","publication_year":2022,"publication_date":"2022-05-30","ids":{"openalex":"https://openalex.org/W4285813893","doi":"https://doi.org/10.1109/iwcmc55113.2022.9825224"},"language":"en","primary_location":{"id":"doi:10.1109/iwcmc55113.2022.9825224","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iwcmc55113.2022.9825224","pdf_url":null,"source":{"id":"https://openalex.org/S4363605313","display_name":"2022 International Wireless Communications and Mobile Computing (IWCMC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Wireless Communications and Mobile Computing (IWCMC)","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/A5084994997","display_name":"Mustafa Al Samara","orcid":"https://orcid.org/0000-0001-6933-7558"},"institutions":[{"id":"https://openalex.org/I2800745255","display_name":"Universit\u00e9 de Haute-Alsace","ror":"https://ror.org/04k8k6n84","country_code":"FR","type":"education","lineage":["https://openalex.org/I2800745255"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Mustafa Al Samara","raw_affiliation_strings":["IRIMAS, University of Haute-Alsace,France","IRIMAS, University of Haute-Alsace, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IRIMAS, University of Haute-Alsace,France","institution_ids":["https://openalex.org/I2800745255"]},{"raw_affiliation_string":"IRIMAS, University of Haute-Alsace, France","institution_ids":["https://openalex.org/I2800745255"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088866073","display_name":"Ismail Bennis","orcid":"https://orcid.org/0000-0001-7470-1094"},"institutions":[{"id":"https://openalex.org/I2800745255","display_name":"Universit\u00e9 de Haute-Alsace","ror":"https://ror.org/04k8k6n84","country_code":"FR","type":"education","lineage":["https://openalex.org/I2800745255"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Ismail Bennis","raw_affiliation_strings":["IRIMAS, University of Haute-Alsace,France","IRIMAS, University of Haute-Alsace, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IRIMAS, University of Haute-Alsace,France","institution_ids":["https://openalex.org/I2800745255"]},{"raw_affiliation_string":"IRIMAS, University of Haute-Alsace, France","institution_ids":["https://openalex.org/I2800745255"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086192057","display_name":"Abdelhafid Aboua\u00efssa","orcid":"https://orcid.org/0000-0003-0459-8081"},"institutions":[{"id":"https://openalex.org/I2800745255","display_name":"Universit\u00e9 de Haute-Alsace","ror":"https://ror.org/04k8k6n84","country_code":"FR","type":"education","lineage":["https://openalex.org/I2800745255"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Abdelhafid Abouaissa","raw_affiliation_strings":["IRIMAS, University of Haute-Alsace,France","IRIMAS, University of Haute-Alsace, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IRIMAS, University of Haute-Alsace,France","institution_ids":["https://openalex.org/I2800745255"]},{"raw_affiliation_string":"IRIMAS, University of Haute-Alsace, France","institution_ids":["https://openalex.org/I2800745255"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071383873","display_name":"Pascal Lorenz","orcid":"https://orcid.org/0000-0003-3346-7216"},"institutions":[{"id":"https://openalex.org/I2800745255","display_name":"Universit\u00e9 de Haute-Alsace","ror":"https://ror.org/04k8k6n84","country_code":"FR","type":"education","lineage":["https://openalex.org/I2800745255"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Pascal Lorenz","raw_affiliation_strings":["IRIMAS, University of Haute-Alsace,France","IRIMAS, University of Haute-Alsace, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IRIMAS, University of Haute-Alsace,France","institution_ids":["https://openalex.org/I2800745255"]},{"raw_affiliation_string":"IRIMAS, University of Haute-Alsace, France","institution_ids":["https://openalex.org/I2800745255"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I2800745255"],"apc_list":null,"apc_paid":null,"fwci":0.5061,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.62783328,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"41","issue":null,"first_page":"784","last_page":"789"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":1.0,"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":1.0,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9959999918937683,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9908999800682068,"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/anomaly-detection","display_name":"Anomaly detection","score":0.7478320002555847},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.7395691871643066},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6701492667198181},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.49715426564216614},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4494849145412445},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.43483296036720276},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3504018783569336}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7478320002555847},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.7395691871643066},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6701492667198181},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.49715426564216614},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4494849145412445},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.43483296036720276},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3504018783569336}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iwcmc55113.2022.9825224","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iwcmc55113.2022.9825224","pdf_url":null,"source":{"id":"https://openalex.org/S4363605313","display_name":"2022 International Wireless Communications and Mobile Computing (IWCMC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Wireless Communications and Mobile Computing (IWCMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1532381193","https://openalex.org/W2010254953","https://openalex.org/W2157568282","https://openalex.org/W2591250285","https://openalex.org/W2625023596","https://openalex.org/W2754384272","https://openalex.org/W2901354261","https://openalex.org/W2997562123","https://openalex.org/W3012037263","https://openalex.org/W3208688400","https://openalex.org/W4206622111","https://openalex.org/W4210515863","https://openalex.org/W4247105055"],"related_works":["https://openalex.org/W2051487156","https://openalex.org/W2073681303","https://openalex.org/W3006513224","https://openalex.org/W2046456988","https://openalex.org/W2499612753","https://openalex.org/W3111802945","https://openalex.org/W2946096271","https://openalex.org/W2295423552","https://openalex.org/W1598471830","https://openalex.org/W3107369729"],"abstract_inverted_index":{"In":[0,67],"today's":[1],"time,":[2],"Wireless":[3],"Sensor":[4],"Networks":[5],"(WSNs)":[6],"and":[7,20,55,59,64,76,92,108,142,160,180,186,198,222],"Internet":[8],"of":[9,16,27,126,145,211],"things":[10],"(IoTs)":[11],"have":[12,48],"attracted":[13],"a":[14,72,89,131,152,174],"lot":[15],"interest":[17],"from":[18,183],"scientific":[19],"businesses":[21],"communities.":[22],"They":[23],"are":[24,45],"made":[25],"up":[26],"limited-resource":[28],"sensors":[29,44],"that":[30,202],"collect":[31],"data":[32,41,106,191],"for":[33,79,116,134,188],"various":[34],"applications":[35],"(medical,":[36],"manufacturing,":[37],"militarily,":[38],"etc.).":[39],"However,":[40],"collected":[42],"by":[43],"susceptible":[46],"to":[47,52,88,95,166],"outliers,":[49],"which":[50],"need":[51],"be":[53],"detected":[54],"classified":[56],"into":[57],"errors":[58,86],"events":[60],"using":[61],"outlier":[62,74,135],"detection":[63,75,136],"classification":[65,77],"methods.":[66],"this":[68],"paper,":[69],"we":[70,172],"propose":[71],"centralized":[73],"approach":[78,154,179],"WSN.":[80],"Our":[81,112],"solution":[82],"can":[83],"distinguish":[84],"between":[85,104,177],"due":[87,94],"faulty":[90],"sensor":[91,110],"those":[93],"an":[96],"event.":[97],"We":[98],"also":[99],"consider":[100],"the":[101,124,127,140,143,146,157,161,168,184,189,203,206],"spatial-temporal":[102],"correlation":[103],"sensors'":[105],"values":[107],"neighbouring":[109],"nodes.":[111],"approach,":[113],"titled":[114],"O2DNC":[115,150,204],"OPTICS-Based":[117],"Outlier":[118],"Detection":[119,215],"with":[120,130,195],"Newton":[121,158],"Classification,":[122],"combines":[123],"benefits":[125],"OPTICS":[128],"algorithm":[129],"new":[132,153],"method":[133],"based":[137,155],"on":[138,156],"computing":[139],"variance":[141],"average":[144],"reachability":[147],"distances.":[148],"Furthermore,":[149],"uses":[151],"interpolation":[159],"K-Nearest":[162],"Neighbours":[163],"(KNN)":[164],"algorithms":[165],"classify":[167],"outliers.":[169],"For":[170],"evaluation,":[171],"conduct":[173],"comparison":[175],"study":[176],"our":[178],"two":[181],"works":[182],"literature":[185],"thus":[187],"multivariate":[190],"case.":[192],"Simulation":[193],"results":[194],"both":[196],"synthetic":[197],"real-life":[199],"datasets":[200],"show":[201],"outperforms":[205],"studied":[207],"techniques":[208],"in":[209],"terms":[210],"several":[212],"metrics":[213],"like":[214],"Rate":[216,220],"(DR),":[217],"False":[218],"Alarm":[219],"(FAR)":[221],"Receiver":[223],"Operating":[224],"Characteristic":[225],"(ROC)":[226],"curve.":[227]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
