{"id":"https://openalex.org/W7217829180","doi":null,"title":"AI-Driven Security Approaches for Detecting Botnet Attacks in IoT Environments","display_name":"AI-Driven Security Approaches for Detecting Botnet Attacks in IoT Environments","publication_year":2025,"publication_date":"2025-10-22","ids":{"openalex":"https://openalex.org/W7217829180"},"language":"en","primary_location":{"id":"pmh:oai:ojs2.utilitasmathematica.com:article/2946","doi":null,"is_oa":true,"landing_page_url":"https://utilitasmathematica.com/index.php/Index/article/view/2946","pdf_url":"https://utilitasmathematica.com/index.php/Index/article/download/2946/811","source":{"id":"https://openalex.org/S124550236","display_name":"Utilitas Mathematica","issn_l":"0315-3681","issn":["0315-3681"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","jufo-1","norway-1","poland-20","russia-white-list-4"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"0315-3681","raw_type":"info:eu-repo/semantics/article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://utilitasmathematica.com/index.php/Index/article/download/2946/811","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5125360328","display_name":"Sridhar Sriharsha Rachakonda","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sridhar Sriharsha Rachakonda","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5118601136","display_name":"Ramesh Lakshmikanth -","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210127875","display_name":"Nvidia (United States)","ror":"https://ror.org/03jdj4y14","country_code":"US","type":"company","lineage":["https://openalex.org/I4210127875"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ramesh Lakshmikanth","raw_affiliation_strings":["Department of Information Technology San Jose , CA , USA","Enterprise Engineering Manager NVIDIA Corporation"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Technology San Jose , CA , USA","institution_ids":[]},{"raw_affiliation_string":"Enterprise Engineering Manager NVIDIA Corporation","institution_ids":["https://openalex.org/I4210127875"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.49625723,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"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/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.00019999999494757503,"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/T12326","display_name":"Network Packet Processing and Optimization","score":9.999999747378752e-05,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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/botnet-detection","display_name":"botnet detection","score":0.9810000061988831},{"id":"https://openalex.org/keywords/iot-security","display_name":"Internet of Things security","score":0.9789999723434448},{"id":"https://openalex.org/keywords/intrusion-detection-systems","display_name":"intrusion detection systems","score":0.9120000004768372},{"id":"https://openalex.org/keywords/mirai","display_name":"Mirai","score":0.8379999995231628},{"id":"https://openalex.org/keywords/class-imbalance","display_name":"class imbalance","score":0.7979999780654907},{"id":"https://openalex.org/keywords/network-flow-features","display_name":"network flow features","score":0.5870000123977661},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"ensemble learning","score":0.5130000114440918},{"id":"https://openalex.org/keywords/xgboost","display_name":"XGBoost","score":0.8759999871253967},{"id":"https://openalex.org/keywords/deep-neural-network","display_name":"deep neural network","score":0.8920000195503235},{"id":"https://openalex.org/keywords/isolation-forest","display_name":"Isolation Forest","score":0.9549999833106995},{"id":"https://openalex.org/keywords/zero-day-attacks","display_name":"zero-day attacks","score":0.7960000038146973},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"anomaly detection","score":0.7699999809265137},{"id":"https://openalex.org/keywords/ddos-attacks","display_name":"DDoS attacks","score":0.6690000295639038}],"concepts":[{"id":"https://openalex.org/C22735295","wikidata":"https://www.wikidata.org/wiki/Q317671","display_name":"Botnet","level":3,"score":0.9280999898910522},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7645999789237976},{"id":"https://openalex.org/C2779585090","wikidata":"https://www.wikidata.org/wiki/Q3457762","display_name":"Resilience (materials science)","level":2,"score":0.6448000073432922},{"id":"https://openalex.org/C81860439","wikidata":"https://www.wikidata.org/wiki/Q251212","display_name":"Internet of Things","level":2,"score":0.5800999999046326},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.5356000065803528},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5238999724388123},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.47600001096725464},{"id":"https://openalex.org/C38822068","wikidata":"https://www.wikidata.org/wiki/Q131406","display_name":"Denial-of-service attack","level":3,"score":0.46880000829696655},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45399999618530273},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.4375},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.3939000070095062},{"id":"https://openalex.org/C182590292","wikidata":"https://www.wikidata.org/wiki/Q989632","display_name":"Network security","level":2,"score":0.38690000772476196},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3831999897956848},{"id":"https://openalex.org/C65856478","wikidata":"https://www.wikidata.org/wiki/Q3991682","display_name":"Attack model","level":2,"score":0.37959998846054077},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3612000048160553},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.35040000081062317},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33180001378059387},{"id":"https://openalex.org/C541664917","wikidata":"https://www.wikidata.org/wiki/Q14001","display_name":"Malware","level":2,"score":0.2962999939918518},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.2743000090122223},{"id":"https://openalex.org/C114809511","wikidata":"https://www.wikidata.org/wiki/Q1412924","display_name":"Flow network","level":2,"score":0.2736000120639801},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.26759999990463257},{"id":"https://openalex.org/C158251709","wikidata":"https://www.wikidata.org/wiki/Q354025","display_name":"Intrusion","level":2,"score":0.2637999951839447},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.2502000033855438}],"mesh":[],"locations_count":1,"locations":[{"id":"pmh:oai:ojs2.utilitasmathematica.com:article/2946","doi":null,"is_oa":true,"landing_page_url":"https://utilitasmathematica.com/index.php/Index/article/view/2946","pdf_url":"https://utilitasmathematica.com/index.php/Index/article/download/2946/811","source":{"id":"https://openalex.org/S124550236","display_name":"Utilitas Mathematica","issn_l":"0315-3681","issn":["0315-3681"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","jufo-1","norway-1","poland-20","russia-white-list-4"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"0315-3681","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"pmh:oai:ojs2.utilitasmathematica.com:article/2946","doi":null,"is_oa":true,"landing_page_url":"https://utilitasmathematica.com/index.php/Index/article/view/2946","pdf_url":"https://utilitasmathematica.com/index.php/Index/article/download/2946/811","source":{"id":"https://openalex.org/S124550236","display_name":"Utilitas Mathematica","issn_l":"0315-3681","issn":["0315-3681"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","jufo-1","norway-1","poland-20","russia-white-list-4"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"0315-3681","raw_type":"info:eu-repo/semantics/article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7217829180.pdf","grobid_xml":"https://content.openalex.org/works/W7217829180.grobid-xml"},"referenced_works_count":1,"referenced_works":["https://openalex.org/W2787957674"],"related_works":["https://openalex.org/W7140592160","https://openalex.org/W4406657951","https://openalex.org/W7218249493","https://openalex.org/W7147065042","https://openalex.org/W7216627700","https://openalex.org/W7168560374","https://openalex.org/W4406356946","https://openalex.org/W7140325522","https://openalex.org/W4415692690","https://openalex.org/W7215836811"],"abstract_inverted_index":{"The":[0,95],"Internet":[1],"of":[2,28,50,82,118,148,183],"Things":[3],"(IoT)":[4],"continues":[5],"to":[6,15,45,187],"expand":[7],"rapidly,":[8],"but":[9],"this":[10],"growth":[11],"also":[12],"exposes":[13],"networks":[14],"sophisticated":[16],"botnet":[17,192],"attacks":[18],"such":[19,162],"as":[20,163],"Mirai":[21],"and":[22,54,84,92,101,111,137,166,174],"Gafgyt":[23],"that":[24,114,129,154],"compromise":[25],"large":[26],"numbers":[27],"devices.":[29],"Intrusion":[30],"Detection":[31],"Systems":[32],"(IDS)":[33],"are":[34],"critical":[35],"for":[36],"securing":[37],"IoT":[38,66,195],"environments.":[39,196],"Yet,":[40],"traditional":[41],"models":[42],"often":[43],"fail":[44],"address":[46],"the":[47,155,181],"dual":[48],"challenges":[49],"extreme":[51],"class":[52],"imbalance":[53],"diverse":[55],"attack":[56,85],"subtypes":[57],"in":[58,194],"real-world":[59],"traffic.":[60],"This":[61,121],"study":[62],"analyzes":[63],"a":[64,124],"large-scale":[65],"IDS":[67],"dataset":[68,96],"containing":[69],"over":[70],"7":[71],"million":[72],"network":[73],"flow":[74],"samples,":[75],"where":[76],"normal":[77],"traffic":[78,86],"constitutes":[79],"only":[80],"8.54%":[81],"records,":[83],"includes":[87],"UDP,":[88],"TCP,":[89],"SYN,":[90],"SCAN,":[91],"ACK":[93],"floods.":[94],"provides":[97],"23":[98],"engineered":[99],"temporal":[100],"relational":[102],"features,":[103],"including":[104],"entropy,":[105],"mutual":[106],"information,":[107],"host-host":[108],"statistics,":[109],"jitter,":[110],"host-port":[112],"behavior":[113],"capture":[115],"subtle":[116],"patterns":[117],"malicious":[119],"activity.":[120],"research":[122],"proposes":[123],"novel":[125],"hybrid":[126],"ensemble":[127],"model":[128,157],"integrates":[130],"cost-sensitive":[131],"LightGBM,":[132],"XGBoost,":[133],"deep":[134],"neural":[135],"networks,":[136],"Isolation":[138],"Forest":[139],"anomaly":[140],"detection,":[141],"combining":[142],"supervised":[143],"learning":[144],"with":[145],"unsupervised":[146],"detection":[147],"zero-day":[149],"threats.":[150],"Experimental":[151],"evaluation":[152],"demonstrates":[153],"proposed":[156],"significantly":[158],"outperforms":[159],"baseline":[160],"approaches":[161],"logistic":[164],"regression":[165],"random":[167],"forests,":[168],"achieving":[169],"superior":[170],"Precision-Recall":[171],"AUC,":[172],"F1-score,":[173],"Matthews":[175],"Correlation":[176],"Coefficient.":[177],"These":[178],"results":[179],"highlight":[180],"potential":[182],"advanced":[184],"AI":[185],"techniques":[186],"enhance":[188],"resilience":[189],"against":[190],"evolving":[191],"threats":[193]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2026-10-03T00:00:00"}
