{"id":"https://openalex.org/W4391769276","doi":"https://doi.org/10.1109/ccwc60891.2024.10427828","title":"Trusting Classifiers with Interpretable Machine Learning Based Feature Selection Backpropagation","display_name":"Trusting Classifiers with Interpretable Machine Learning Based Feature Selection Backpropagation","publication_year":2024,"publication_date":"2024-01-08","ids":{"openalex":"https://openalex.org/W4391769276","doi":"https://doi.org/10.1109/ccwc60891.2024.10427828"},"language":"en","primary_location":{"id":"doi:10.1109/ccwc60891.2024.10427828","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccwc60891.2024.10427828","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 14th Annual Computing and Communication Workshop and Conference (CCWC)","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/A5101694872","display_name":"Saikat Das","orcid":"https://orcid.org/0000-0003-1142-8259"},"institutions":[{"id":"https://openalex.org/I197572798","display_name":"Utah Valley University","ror":"https://ror.org/02rxpxc98","country_code":"US","type":"education","lineage":["https://openalex.org/I197572798"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Saikat Das","raw_affiliation_strings":["Utah Valley University,Department of Computer Scinece,Orem,UT,USA","Department of Computer Scinece, Utah Valley University, Orem, UT, USA"],"affiliations":[{"raw_affiliation_string":"Utah Valley University,Department of Computer Scinece,Orem,UT,USA","institution_ids":["https://openalex.org/I197572798"]},{"raw_affiliation_string":"Department of Computer Scinece, Utah Valley University, Orem, UT, USA","institution_ids":["https://openalex.org/I197572798"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020873617","display_name":"Raktim Ranjan Das","orcid":null},"institutions":[{"id":"https://openalex.org/I32883739","display_name":"Stamford University Bangladesh","ror":"https://ror.org/0441jdk54","country_code":"BD","type":"education","lineage":["https://openalex.org/I32883739"]}],"countries":["BD"],"is_corresponding":false,"raw_author_name":"Raktim Ranjan Das","raw_affiliation_strings":["Stamford University,Department of Computer Science and Engineering,Bangladesh","Department of Computer Science and Engineering, Stamford University, Bangladesh"],"affiliations":[{"raw_affiliation_string":"Stamford University,Department of Computer Science and Engineering,Bangladesh","institution_ids":["https://openalex.org/I32883739"]},{"raw_affiliation_string":"Department of Computer Science and Engineering, Stamford University, Bangladesh","institution_ids":["https://openalex.org/I32883739"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019549865","display_name":"Frederick T. Sheldon","orcid":"https://orcid.org/0000-0003-1241-2750"},"institutions":[{"id":"https://openalex.org/I155093810","display_name":"University of Idaho","ror":"https://ror.org/03hbp5t65","country_code":"US","type":"education","lineage":["https://openalex.org/I155093810"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Frederick T. Sheldon","raw_affiliation_strings":["University of Idaho,Department of Computer Science,Moscow,ID,USA","Department of Computer Science, University of Idaho, Moscow, ID, USA"],"affiliations":[{"raw_affiliation_string":"University of Idaho,Department of Computer Science,Moscow,ID,USA","institution_ids":["https://openalex.org/I155093810"]},{"raw_affiliation_string":"Department of Computer Science, University of Idaho, Moscow, ID, USA","institution_ids":["https://openalex.org/I155093810"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012148704","display_name":"Sajjan G. Shiva","orcid":"https://orcid.org/0000-0002-3996-7484"},"institutions":[{"id":"https://openalex.org/I94658018","display_name":"University of Memphis","ror":"https://ror.org/01cq23130","country_code":"US","type":"education","lineage":["https://openalex.org/I94658018"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sajjan Shiva","raw_affiliation_strings":["The University of Memphis,Department of Computer Science,Memphis,TN,USA","Department of Computer Science, The University of Memphis, Memphis, TN, USA"],"affiliations":[{"raw_affiliation_string":"The University of Memphis,Department of Computer Science,Memphis,TN,USA","institution_ids":["https://openalex.org/I94658018"]},{"raw_affiliation_string":"Department of Computer Science, The University of Memphis, Memphis, TN, USA","institution_ids":["https://openalex.org/I94658018"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101694872"],"corresponding_institution_ids":["https://openalex.org/I197572798"],"apc_list":null,"apc_paid":null,"fwci":0.3663,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.54601986,"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":"0527","last_page":"0533"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9986000061035156,"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":0.9937999844551086,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.8028861284255981},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.7917196750640869},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7899588346481323},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.7384536266326904},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6877995729446411},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6019987463951111},{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.48735150694847107},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.45493966341018677},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.43991607427597046},{"id":"https://openalex.org/keywords/denial-of-service-attack","display_name":"Denial-of-service attack","score":0.41921740770339966},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.41714048385620117},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3246927857398987}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8028861284255981},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.7917196750640869},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7899588346481323},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.7384536266326904},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6877995729446411},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6019987463951111},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.48735150694847107},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.45493966341018677},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.43991607427597046},{"id":"https://openalex.org/C38822068","wikidata":"https://www.wikidata.org/wiki/Q131406","display_name":"Denial-of-service attack","level":3,"score":0.41921740770339966},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.41714048385620117},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3246927857398987},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","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:10.1109/ccwc60891.2024.10427828","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccwc60891.2024.10427828","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 14th Annual Computing and Communication Workshop and Conference (CCWC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.4099999964237213,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1598874232","https://openalex.org/W2016070752","https://openalex.org/W2076384720","https://openalex.org/W2087016914","https://openalex.org/W2089468765","https://openalex.org/W2099940443","https://openalex.org/W2101234009","https://openalex.org/W2114834796","https://openalex.org/W2128728535","https://openalex.org/W2130949063","https://openalex.org/W2167101736","https://openalex.org/W2198302135","https://openalex.org/W2230781190","https://openalex.org/W2267339884","https://openalex.org/W2516809705","https://openalex.org/W2546923044","https://openalex.org/W2550999023","https://openalex.org/W2759242272","https://openalex.org/W2979590797","https://openalex.org/W3006579283","https://openalex.org/W3080798771","https://openalex.org/W3118722953","https://openalex.org/W4249247926"],"related_works":["https://openalex.org/W4388745254","https://openalex.org/W2980082554","https://openalex.org/W1517228774","https://openalex.org/W2767419625","https://openalex.org/W2389704471","https://openalex.org/W2944292463","https://openalex.org/W3014252901","https://openalex.org/W2188759683","https://openalex.org/W4317376680","https://openalex.org/W4360777922"],"abstract_inverted_index":{"In":[0,62],"a":[1,9,60,67,103],"machine":[2,75],"learning":[3,76],"classification":[4,32],"problem,":[5],"feature":[6,69,114],"selection":[7,70,115],"is":[8,98,128],"required":[10],"pre-processing":[11],"phase":[12,116],"which":[13],"identifies":[14],"important":[15],"and":[16,28,167,176],"relevant":[17,83,108],"features":[18,58,84,109,139],"from":[19,59,141],"the":[20,25,30,56,81,91,113,119,132,137,155,158],"dataset":[21],"to":[22,54,79,101,117,130,181],"potentially":[23],"reduce":[24],"computational":[26],"complexity":[27],"improves":[29],"overall":[31],"performances.":[33],"Feature":[34],"reduction":[35],"mechanisms,":[36],"such":[37],"as":[38],"Information":[39],"Gain,":[40],"Gain":[41],"Ratio,":[42],"Chi-squared,":[43],"ReliefF,":[44],"Deep":[45],"Learning,":[46],"etc.":[47],"along":[48],"with":[49],"domain":[50],"knowledge":[51],"are":[52,110,189],"used":[53,100,111,129],"find":[55,80],"appropriate":[57],"dataset.":[61],"this":[63,96,142],"paper,":[64],"we":[65,144],"propose":[66],"novel":[68],"process":[71],"based":[72],"on":[73,90],"interpretable":[74],"technique":[77,97],"(IMLFS)":[78],"optimal":[82],"in":[85,112],"detecting":[86],"DDoS":[87,105],"cyber-attacks.":[88],"Based":[89],"effectiveness":[92],"of":[93,157],"critical":[94],"features,":[95],"also":[99],"explain":[102],"detected":[104],"attack.":[106],"These":[107],"retrain":[118],"model":[120,177],"for":[121],"better":[122],"accuracy.":[123],"The":[124],"benchmark":[125],"dataset,":[126,143],"NSL-KDD":[127],"evaluate":[131],"proposed":[133],"approach.":[134],"Moreover,":[135],"using":[136],"extracted":[138],"obtained":[140],"investigated":[145],"our":[146],"recently":[147],"developed":[148],"ensemble":[149],"supervised":[150],"framework.":[151],"This":[152],"investigation":[153],"confirms":[154],"efficacy":[156],"IMLFS":[159],"approach":[160],"by":[161],"producing":[162],"both":[163],"higher":[164],"detection":[165],"accuracy":[166,175],"lower":[168],"false":[169],"positive":[170],"alarms.":[171],"A":[172],"significant":[173],"improved":[174],"training":[178],"times":[179],"compared":[180,185],"earlier":[182],"studies":[183],"that":[184],"various":[186],"IML":[187],"methods":[188],"reported":[190],"here.":[191]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}