{"id":"https://openalex.org/W4414948982","doi":"https://doi.org/10.1007/s10462-025-11358-9","title":"CTWA: a novel incremental deep learning-based intrusion detection method for the Internet of Things","display_name":"CTWA: a novel incremental deep learning-based intrusion detection method for the Internet of Things","publication_year":2025,"publication_date":"2025-10-08","ids":{"openalex":"https://openalex.org/W4414948982","doi":"https://doi.org/10.1007/s10462-025-11358-9"},"language":"en","primary_location":{"id":"doi:10.1007/s10462-025-11358-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10462-025-11358-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10462-025-11358-9.pdf","source":{"id":"https://openalex.org/S122814990","display_name":"Artificial Intelligence Review","issn_l":"0269-2821","issn":["0269-2821","1573-7462"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Artificial Intelligence Review","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s10462-025-11358-9.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101496773","display_name":"Haizhen Wang","orcid":"https://orcid.org/0000-0002-5509-1355"},"institutions":[{"id":"https://openalex.org/I111971639","display_name":"Qiqihar University","ror":"https://ror.org/01khf5d59","country_code":"CN","type":"education","lineage":["https://openalex.org/I111971639"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Haizhen Wang","raw_affiliation_strings":["College of Computer and Control Engineering, Qiqihar University, Qiqihar, 161006, China","Heilongjiang Key Laboratory of Big Data Network Security Detection and Analysis, Qiqihar University, Qiqihar, 161006, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer and Control Engineering, Qiqihar University, Qiqihar, 161006, China","institution_ids":["https://openalex.org/I111971639"]},{"raw_affiliation_string":"Heilongjiang Key Laboratory of Big Data Network Security Detection and Analysis, Qiqihar University, Qiqihar, 161006, China","institution_ids":["https://openalex.org/I111971639"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100305490","display_name":"Yutong Yang","orcid":"https://orcid.org/0000-0001-9074-756X"},"institutions":[{"id":"https://openalex.org/I111971639","display_name":"Qiqihar University","ror":"https://ror.org/01khf5d59","country_code":"CN","type":"education","lineage":["https://openalex.org/I111971639"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yutong Yang","raw_affiliation_strings":["College of Computer and Control Engineering, Qiqihar University, Qiqihar, 161006, China","Heilongjiang Key Laboratory of Big Data Network Security Detection and Analysis, Qiqihar University, Qiqihar, 161006, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer and Control Engineering, Qiqihar University, Qiqihar, 161006, China","institution_ids":["https://openalex.org/I111971639"]},{"raw_affiliation_string":"Heilongjiang Key Laboratory of Big Data Network Security Detection and Analysis, Qiqihar University, Qiqihar, 161006, China","institution_ids":["https://openalex.org/I111971639"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074042731","display_name":"Pan Tan","orcid":"https://orcid.org/0000-0003-3919-5805"},"institutions":[{"id":"https://openalex.org/I111971639","display_name":"Qiqihar University","ror":"https://ror.org/01khf5d59","country_code":"CN","type":"education","lineage":["https://openalex.org/I111971639"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pan Tan","raw_affiliation_strings":["College of Computer and Control Engineering, Qiqihar University, Qiqihar, 161006, China","Heilongjiang Key Laboratory of Big Data Network Security Detection and Analysis, Qiqihar University, Qiqihar, 161006, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer and Control Engineering, Qiqihar University, Qiqihar, 161006, China","institution_ids":["https://openalex.org/I111971639"]},{"raw_affiliation_string":"Heilongjiang Key Laboratory of Big Data Network Security Detection and Analysis, Qiqihar University, Qiqihar, 161006, China","institution_ids":["https://openalex.org/I111971639"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5101496773"],"corresponding_institution_ids":["https://openalex.org/I111971639"],"apc_list":{"value":3090,"currency":"USD","value_usd":3090},"apc_paid":{"value":3090,"currency":"USD","value_usd":3090},"fwci":0.6641,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.75073109,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"58","issue":"12","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":1.0,"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":1.0,"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":0.9987999796867371,"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/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9958000183105469,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/forgetting","display_name":"Forgetting","score":0.6351000070571899},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.573199987411499},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.48410001397132874},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4749999940395355},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.47380000352859497},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.4422999918460846},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.43290001153945923},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4124000072479248},{"id":"https://openalex.org/keywords/intrusion-detection-system","display_name":"Intrusion detection system","score":0.4117000102996826}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.867900013923645},{"id":"https://openalex.org/C7149132","wikidata":"https://www.wikidata.org/wiki/Q1377840","display_name":"Forgetting","level":2,"score":0.6351000070571899},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6014999747276306},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.573199987411499},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5242000222206116},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.48410001397132874},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4749999940395355},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.47380000352859497},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4422999918460846},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.43290001153945923},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4124000072479248},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.4117000102996826},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.40860000252723694},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.39469999074935913},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.34459999203681946},{"id":"https://openalex.org/C107418235","wikidata":"https://www.wikidata.org/wiki/Q1520565","display_name":"Human multitasking","level":2,"score":0.3384000062942505},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.33480000495910645},{"id":"https://openalex.org/C28006648","wikidata":"https://www.wikidata.org/wiki/Q6934509","display_name":"Multi-task learning","level":3,"score":0.3330000042915344},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3314000070095062},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.3292999863624573},{"id":"https://openalex.org/C2780735816","wikidata":"https://www.wikidata.org/wiki/Q28324931","display_name":"Incremental learning","level":2,"score":0.3199999928474426},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.30320000648498535},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.275299996137619},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.27320000529289246},{"id":"https://openalex.org/C7218915","wikidata":"https://www.wikidata.org/wiki/Q1054475","display_name":"Gaussian function","level":3,"score":0.260699987411499},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.25920000672340393},{"id":"https://openalex.org/C81860439","wikidata":"https://www.wikidata.org/wiki/Q251212","display_name":"Internet of Things","level":2,"score":0.25619998574256897},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.25270000100135803}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s10462-025-11358-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10462-025-11358-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10462-025-11358-9.pdf","source":{"id":"https://openalex.org/S122814990","display_name":"Artificial Intelligence Review","issn_l":"0269-2821","issn":["0269-2821","1573-7462"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Artificial Intelligence Review","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s10462-025-11358-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10462-025-11358-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10462-025-11358-9.pdf","source":{"id":"https://openalex.org/S122814990","display_name":"Artificial Intelligence Review","issn_l":"0269-2821","issn":["0269-2821","1573-7462"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Artificial Intelligence Review","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4414948982.pdf","grobid_xml":"https://content.openalex.org/works/W4414948982.grobid-xml"},"referenced_works_count":25,"referenced_works":["https://openalex.org/W52756503","https://openalex.org/W2473930607","https://openalex.org/W2560647685","https://openalex.org/W2889165715","https://openalex.org/W2954929116","https://openalex.org/W2963540014","https://openalex.org/W2963748489","https://openalex.org/W2978822875","https://openalex.org/W3123883043","https://openalex.org/W3140236729","https://openalex.org/W3210654422","https://openalex.org/W4225795437","https://openalex.org/W4287204993","https://openalex.org/W4290755975","https://openalex.org/W4296367487","https://openalex.org/W4309957189","https://openalex.org/W4313028293","https://openalex.org/W4360836770","https://openalex.org/W4366776064","https://openalex.org/W4376253650","https://openalex.org/W4381249272","https://openalex.org/W4382281941","https://openalex.org/W4383046856","https://openalex.org/W4383750832","https://openalex.org/W7102813069"],"related_works":[],"abstract_inverted_index":{"Class":[0],"incremental":[1,10,20,57,85,119],"learning":[2,86,120,144],"aims":[3],"to":[4,41,92,95,141,172,191],"learn":[5],"new":[6,127,146,164],"courses":[7],"in":[8,55,118,151,214,270],"an":[9],"manner":[11],"without":[12],"forgetting":[13,152],"the":[14,43,63,66,84,93,97,101,145,153,156,160,174,193,210,233,247,271],"categories":[15],"previously":[16],"learned.":[17],"A":[18],"novel":[19],"Internet":[21],"of":[22,45,65,74,100,155,162,216,264,273],"Things":[23],"(IoT)":[24],"intrusion":[25],"detection":[26],"method":[27,60,254],"CTWA":[28],"based":[29],"on":[30,199,205],"Convolutional":[31,36],"Autoencoder":[32],"(CAE)":[33],"and":[34,52,70,79,81,103,126,132,165,170,185,220,226,261],"Temporal":[35],"Network":[37],"(TCN)":[38],"is":[39,189,236,240,249],"proposed":[40,211,253],"address":[42],"issues":[44],"insufficient":[46],"generalization":[47],"ability,":[48],"high":[49],"computational":[50],"resources,":[51],"redundant":[53],"features":[54,73],"class":[56],"learning.":[58],"This":[59],"first":[61],"completes":[62],"training":[64,98,231],"CAE-TCN":[67,109],"module,":[68],"extracts":[69],"concatenates":[71],"local":[72],"data":[75],"samples":[76],"through":[77,115],"CAE":[78,94],"TCN,":[80],"then":[82],"initializes":[83],"module.":[87,121],"Residual":[88],"modules":[89],"are":[90,168],"added":[91],"improve":[96],"effect":[99],"model":[102,212],"avoid":[104],"gradient":[105],"vanishing":[106],"problems.":[107],"The":[108,202,252],"module":[110],"shares":[111],"lower-level":[112],"feature":[113],"representations":[114],"task-specific":[116],"layers":[117],"It":[122],"distinguishes":[123,257],"between":[124,138,258],"old":[125,157,166],"tasks":[128,167],"using":[129],"Gaussian":[130],"distribution,":[131],"applies":[133],"Weight":[134],"alignment":[135],"(WA)":[136],"techniques":[137],"task":[139,147],"heads":[140],"ensure":[142,173],"that":[143,209],"does":[148],"not":[149],"result":[150],"knowledge":[154],"tasks.":[158],"Ultimately,":[159],"outputs":[161],"both":[163],"weighted":[169],"fused":[171],"optimal":[175],"classification":[176],"result.":[177],"Additionally,":[178],"a":[179],"loss":[180,184,188],"function":[181],"combining":[182],"cross-entropy":[183],"label":[186],"smoothing":[187],"used":[190],"enhance":[192],"model\u2019s":[194,234],"performance.":[195],"We":[196],"conducted":[197],"experiments":[198],"two":[200],"datasets.":[201],"experimental":[203],"results":[204],"CICIoT2023":[206],"dataset":[207],"demonstrate":[208],"excels":[213],"terms":[215],"accuracy,":[217],"precision,":[218],"recall,":[219],"F1-Score,":[221],"achieving":[222],"0.9643,":[223,225],"0.9659,":[224],"0.9645,":[227],"respectively.":[228],"With":[229],"40":[230],"epochs,":[232],"runtime":[235],"789.58":[237],"s,":[238],"which":[239],"higher":[241],"than":[242],"most":[243],"comparison":[244],"models,":[245],"but":[246],"accuracy":[248],"significantly":[250],"improved.":[251],"can":[255],"effectively":[256],"different":[259],"known":[260],"unknown":[262],"types":[263],"attacks,":[265],"highlighting":[266],"its":[267],"potential":[268],"applications":[269],"field":[272],"cybersecurity.":[274]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-08-04T08:18:43.703281","created_date":"2025-10-10T00:00:00"}