{"id":"https://openalex.org/W4401609055","doi":"https://doi.org/10.23919/ifipnetworking62109.2024.10619794","title":"A Data-Driven Solution for Improving Transferability of Traffic Flow Feature Selection","display_name":"A Data-Driven Solution for Improving Transferability of Traffic Flow Feature Selection","publication_year":2024,"publication_date":"2024-06-03","ids":{"openalex":"https://openalex.org/W4401609055","doi":"https://doi.org/10.23919/ifipnetworking62109.2024.10619794"},"language":"en","primary_location":{"id":"doi:10.23919/ifipnetworking62109.2024.10619794","is_oa":false,"landing_page_url":"http://dx.doi.org/10.23919/ifipnetworking62109.2024.10619794","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IFIP Networking Conference (IFIP Networking)","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/A5070682118","display_name":"Pegah Golchin","orcid":"https://orcid.org/0000-0002-8686-113X"},"institutions":[{"id":"https://openalex.org/I31512782","display_name":"Technical University of Darmstadt","ror":"https://ror.org/05n911h24","country_code":"DE","type":"education","lineage":["https://openalex.org/I31512782"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Pegah Golchin","raw_affiliation_strings":["Technical University of Darmstadt,Multimedia Communications Lab (KOM),Germany"],"affiliations":[{"raw_affiliation_string":"Technical University of Darmstadt,Multimedia Communications Lab (KOM),Germany","institution_ids":["https://openalex.org/I31512782"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017658581","display_name":"Nima Rafiee","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nima Rafiee","raw_affiliation_strings":["Zalando,Berlin,Germany"],"affiliations":[{"raw_affiliation_string":"Zalando,Berlin,Germany","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035795457","display_name":"Ralf Kundel","orcid":"https://orcid.org/0000-0003-1711-5990"},"institutions":[{"id":"https://openalex.org/I31512782","display_name":"Technical University of Darmstadt","ror":"https://ror.org/05n911h24","country_code":"DE","type":"education","lineage":["https://openalex.org/I31512782"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Ralf Kundel","raw_affiliation_strings":["Technical University of Darmstadt,Multimedia Communications Lab (KOM),Germany"],"affiliations":[{"raw_affiliation_string":"Technical University of Darmstadt,Multimedia Communications Lab (KOM),Germany","institution_ids":["https://openalex.org/I31512782"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5070682118"],"corresponding_institution_ids":["https://openalex.org/I31512782"],"apc_list":null,"apc_paid":null,"fwci":0.2787,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.556822,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"592","last_page":"594"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T10320","display_name":"Neural Networks and Applications","score":0.9776999950408936,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9490000009536743,"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/transferability","display_name":"Transferability","score":0.8676090836524963},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7209905982017517},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.6165692806243896},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5326290726661682},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.46733176708221436},{"id":"https://openalex.org/keywords/flow","display_name":"Flow (mathematics)","score":0.4639894962310791},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4223243296146393},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.41866326332092285},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.25174757838249207},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.22683244943618774},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.20433664321899414},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.06884637475013733}],"concepts":[{"id":"https://openalex.org/C61272859","wikidata":"https://www.wikidata.org/wiki/Q7834031","display_name":"Transferability","level":3,"score":0.8676090836524963},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7209905982017517},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.6165692806243896},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5326290726661682},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.46733176708221436},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.4639894962310791},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4223243296146393},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41866326332092285},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.25174757838249207},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.22683244943618774},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.20433664321899414},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.06884637475013733},{"id":"https://openalex.org/C140331021","wikidata":"https://www.wikidata.org/wiki/Q1868104","display_name":"Logit","level":2,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/ifipnetworking62109.2024.10619794","is_oa":false,"landing_page_url":"http://dx.doi.org/10.23919/ifipnetworking62109.2024.10619794","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IFIP Networking Conference (IFIP Networking)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W2076384720","https://openalex.org/W2077488147","https://openalex.org/W2093331366","https://openalex.org/W2124833832","https://openalex.org/W2296509296","https://openalex.org/W2767863364","https://openalex.org/W2789828921","https://openalex.org/W3035510612","https://openalex.org/W4205088899","https://openalex.org/W4281719610","https://openalex.org/W4381734333","https://openalex.org/W4382654565","https://openalex.org/W4389077804","https://openalex.org/W6734796896","https://openalex.org/W7018627815"],"related_works":["https://openalex.org/W4399895933","https://openalex.org/W2161221533","https://openalex.org/W4229699405","https://openalex.org/W1666484574","https://openalex.org/W2216382288","https://openalex.org/W2355491300","https://openalex.org/W4372266204","https://openalex.org/W4386564352","https://openalex.org/W2952668426","https://openalex.org/W3000039163"],"abstract_inverted_index":{"The":[0,75],"expansion":[1],"of":[2,120,138],"Internet":[3],"connectivity":[4],"has":[5],"increased":[6],"cyber":[7],"threats":[8],"in":[9,54,93,135],"computer":[10],"networks.":[11],"Machine":[12],"Learning":[13],"(ML)-based":[14],"Intrusion":[15],"Detection":[16],"Systems":[17],"(IDS)":[18],"have":[19],"emerged":[20],"as":[21],"a":[22,45,110],"promising":[23],"candidate,":[24],"leveraging":[25],"ML":[26,43,69],"models":[27],"to":[28,57,79,91,116,140],"analyze":[29],"network":[30,84,96,126,150],"traffic":[31,85,127,151],"features":[32,62,77,123],"and":[33,37,71,98,143,159],"differentiate":[34],"between":[35],"malicious":[36],"benign":[38],"flows.":[39],"However,":[40],"before":[41],"using":[42],"models,":[44,70,162],"crucial":[46],"preprocessing":[47],"step":[48],"called":[49],"feature":[50],"selection":[51],"is":[52,88],"performed":[53],"ML-based":[55],"IDS":[56],"identify":[58],"the":[59,118,121,154],"most":[60],"relevant":[61],"that":[63],"can":[64],"enhance":[65],"detection":[66,136],"accuracy,":[67],"streamline":[68],"reduce":[72],"computational":[73],"complexity.":[74],"selected":[76,122],"need":[78],"be":[80],"transferable":[81],"across":[82,124,145],"diverse":[83],"datasets,":[86],"which":[87],"challenging":[89],"due":[90],"variations":[92],"attack":[94],"types,":[95],"architectures,":[97],"complex":[99],"relationships":[100],"among":[101],"their":[102],"flow":[103],"features.":[104],"In":[105],"this":[106],"work,":[107],"we":[108],"present":[109],"Data-Driven":[111],"Ensemble":[112],"Feature":[113],"Selection":[114],"(DD-EFS)":[115],"improve":[117],"transferability":[119],"various":[125],"datasets.":[128],"Our":[129],"results":[130],"demonstrate":[131],"an":[132],"average":[133],"increase":[134],"performance":[137],"up":[139],"6.8%,":[141],"5.1%,":[142],"4.3%":[144],"two":[146],"distinct,":[147],"previously":[148],"unseen":[149],"datasets":[152],"for":[153],"Random":[155],"Forest,":[156],"Logistic":[157],"Regression,":[158],"Multi-Layer":[160],"Perceptron":[161],"respectively.":[163]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-12-23T23:11:35.936235","created_date":"2025-10-10T00:00:00"}