{"id":"https://openalex.org/W4206297860","doi":"https://doi.org/10.1109/uemcon53757.2021.9666581","title":"A Comparative Study of Machine Learning Models for Cyber-attacks Detection in Wireless Sensor Networks","display_name":"A Comparative Study of Machine Learning Models for Cyber-attacks Detection in Wireless Sensor Networks","publication_year":2021,"publication_date":"2021-12-01","ids":{"openalex":"https://openalex.org/W4206297860","doi":"https://doi.org/10.1109/uemcon53757.2021.9666581"},"language":"en","primary_location":{"id":"doi:10.1109/uemcon53757.2021.9666581","is_oa":false,"landing_page_url":"https://doi.org/10.1109/uemcon53757.2021.9666581","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","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/A5029165876","display_name":"Shereen Ismail","orcid":"https://orcid.org/0000-0001-8580-1648"},"institutions":[{"id":"https://openalex.org/I24571045","display_name":"University of North Dakota","ror":"https://ror.org/04a5szx83","country_code":"US","type":"education","lineage":["https://openalex.org/I24571045"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Shereen Ismail","raw_affiliation_strings":["School of Electrical Engineering and Computer Science, University of North Dakota, Grand Forks, ND, USA"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Computer Science, University of North Dakota, Grand Forks, ND, USA","institution_ids":["https://openalex.org/I24571045"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019676675","display_name":"Tala Talaei Khoei","orcid":"https://orcid.org/0000-0002-7630-9034"},"institutions":[{"id":"https://openalex.org/I24571045","display_name":"University of North Dakota","ror":"https://ror.org/04a5szx83","country_code":"US","type":"education","lineage":["https://openalex.org/I24571045"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tala Talaei Khoei","raw_affiliation_strings":["School of Electrical Engineering and Computer Science, University of North Dakota, Grand Forks, ND, USA"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Computer Science, University of North Dakota, Grand Forks, ND, USA","institution_ids":["https://openalex.org/I24571045"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108107118","display_name":"Ronald Marsh","orcid":null},"institutions":[{"id":"https://openalex.org/I24571045","display_name":"University of North Dakota","ror":"https://ror.org/04a5szx83","country_code":"US","type":"education","lineage":["https://openalex.org/I24571045"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ronald Marsh","raw_affiliation_strings":["School of Electrical Engineering and Computer Science, University of North Dakota, Grand Forks, ND, USA"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Computer Science, University of North Dakota, Grand Forks, ND, USA","institution_ids":["https://openalex.org/I24571045"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071211423","display_name":"Naima Kaabouch","orcid":null},"institutions":[{"id":"https://openalex.org/I24571045","display_name":"University of North Dakota","ror":"https://ror.org/04a5szx83","country_code":"US","type":"education","lineage":["https://openalex.org/I24571045"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Naima Kaabouch","raw_affiliation_strings":["School of Electrical Engineering and Computer Science, University of North Dakota, Grand Forks, ND, USA"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Computer Science, University of North Dakota, Grand Forks, ND, USA","institution_ids":["https://openalex.org/I24571045"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5029165876"],"corresponding_institution_ids":["https://openalex.org/I24571045"],"apc_list":null,"apc_paid":null,"fwci":4.7371,"has_fulltext":false,"cited_by_count":38,"citation_normalized_percentile":{"value":0.95156784,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"0313","last_page":"0318"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9994999766349792,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9994999766349792,"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/T11498","display_name":"Security in Wireless Sensor Networks","score":0.9976999759674072,"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":0.9970999956130981,"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/computer-science","display_name":"Computer science","score":0.8128372430801392},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.692125678062439},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6427408456802368},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5170248746871948},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5098347067832947},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.503485381603241},{"id":"https://openalex.org/keywords/wireless-sensor-network","display_name":"Wireless sensor network","score":0.4972420036792755},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.4777340590953827},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.11048942804336548}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8128372430801392},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.692125678062439},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6427408456802368},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5170248746871948},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5098347067832947},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.503485381603241},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.4972420036792755},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.4777340590953827},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.11048942804336548}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/uemcon53757.2021.9666581","is_oa":false,"landing_page_url":"https://doi.org/10.1109/uemcon53757.2021.9666581","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7799999713897705,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W2033426860","https://openalex.org/W2345946976","https://openalex.org/W2498181172","https://openalex.org/W2525336835","https://openalex.org/W2773791445","https://openalex.org/W2792483895","https://openalex.org/W2810018695","https://openalex.org/W2907502017","https://openalex.org/W2910232368","https://openalex.org/W2947123069","https://openalex.org/W2963694286","https://openalex.org/W3004018737","https://openalex.org/W3006165800","https://openalex.org/W3092236329","https://openalex.org/W3190742248","https://openalex.org/W3194535035"],"related_works":["https://openalex.org/W3036202055","https://openalex.org/W3213126983","https://openalex.org/W3017044142","https://openalex.org/W2955385375","https://openalex.org/W4225360065","https://openalex.org/W3100297620","https://openalex.org/W3165907317","https://openalex.org/W4293525103","https://openalex.org/W3195168932","https://openalex.org/W4224277717"],"abstract_inverted_index":{"Wireless":[0],"Sensor":[1],"Network":[2],"is":[3,13,52,139,172],"a":[4,23,34,69],"key":[5],"technology":[6],"for":[7,64,81,141],"Internet":[8],"of":[9,16,26,41,54,75,90,106,158,168,176,179,182,186],"Things,":[10],"but":[11],"it":[12],"an":[14,128],"example":[15],"energy-restricted":[17],"networks.":[18],"In":[19],"such":[20,48],"networks":[21],"with":[22,29],"large":[24],"number":[25],"deployed":[27],"sensors":[28],"limited":[30],"capabilities,":[31],"security":[32],"becomes":[33],"crucial":[35],"concern":[36],"which":[37],"requires":[38],"proper":[39],"design":[40,60],"detection":[42,62,83],"and":[43,72,98,117,124,132,163,192],"mitigation":[44],"techniques":[45,80],"that":[46,150],"address":[47],"challenge.":[49],"Machine":[50],"learning":[51,78,111],"one":[53],"the":[55,88,146,169],"most":[56],"efficient":[57],"ways":[58],"to":[59,104,155],"cyber-attacks":[61,82],"systems":[63],"WSN.":[65,85],"This":[66],"paper":[67],"presents":[68],"comparative":[70],"study":[71],"performance":[73,89,167],"analysis":[74],"different":[76],"machine":[77,110],"classification":[79],"in":[84,174],"We":[86,119,144],"investigate":[87],"three":[91,107],"recent":[92],"boosting":[93],"techniques,":[94],"namely":[95,113],"GBM,":[96],"LightGBM,":[97],"Catboost.":[99],"Their":[100],"performances":[101],"are":[102],"compared":[103],"those":[105],"commonly":[108],"known":[109],"methods,":[112],"Gaussian":[114],"NB,":[115],"KNN,":[116],"RF.":[118],"apply":[120],"both":[121],"Pearson\u2019s":[122],"correlation":[123],"mutual":[125],"information":[126],"as":[127],"ensemble":[129],"feature":[130],"selection":[131],"dimensionality":[133],"reduction.":[134],"Tree-based":[135],"Pipeline":[136],"Optimization":[137],"Tool":[138],"utilized":[140],"hyperparameter":[142],"tuning.":[143],"use":[145],"specialized":[147],"dataset,":[148],"WSN-DS,":[149],"contains":[151],"numerous":[152],"samples":[153],"corresponding":[154],"four":[156],"kinds":[157],"attacks:":[159],"Grayhole,":[160],"Blackhole,":[161],"Flooding,":[162],"TDMA":[164],"scheduling.":[165],"The":[166],"six":[170],"models":[171],"investigated":[173],"terms":[175],"accuracy,":[177],"probability":[178,181,185],"detection,":[180],"false":[183],"alarm,":[184],"misdetection,":[187],"memory":[188],"usage,":[189],"processing":[190],"time,":[191],"average":[193],"prediction":[194],"time":[195],"per":[196],"sample.":[197]},"counts_by_year":[{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":14},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":9}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}