{"id":"https://openalex.org/W4318185151","doi":"https://doi.org/10.1109/bigdata55660.2022.10020393","title":"OOG- Optuna Optimized GAN Sampling Technique for Tabular Imbalanced Malware Data","display_name":"OOG- Optuna Optimized GAN Sampling Technique for Tabular Imbalanced Malware Data","publication_year":2022,"publication_date":"2022-12-17","ids":{"openalex":"https://openalex.org/W4318185151","doi":"https://doi.org/10.1109/bigdata55660.2022.10020393"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata55660.2022.10020393","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/bigdata55660.2022.10020393","pdf_url":null,"source":{"id":"https://openalex.org/S4363607709","display_name":"2022 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Big Data (Big Data)","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/A5014921097","display_name":"S. M Towhidul Islam Tonmoy","orcid":null},"institutions":[{"id":"https://openalex.org/I59805279","display_name":"Islamic University of Technology","ror":"https://ror.org/057gnqw22","country_code":"BD","type":"education","lineage":["https://openalex.org/I59805279"]}],"countries":["BD"],"is_corresponding":true,"raw_author_name":"S. M Towhidul Islam Tonmoy","raw_affiliation_strings":["Islamic University of Technology,Department of Electrical and Electronic Engineering,Gazipur,Bangladesh,1704"],"affiliations":[{"raw_affiliation_string":"Islamic University of Technology,Department of Electrical and Electronic Engineering,Gazipur,Bangladesh,1704","institution_ids":["https://openalex.org/I59805279"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102836237","display_name":"S M Mehedi Zaman","orcid":"https://orcid.org/0000-0001-7841-3962"},"institutions":[{"id":"https://openalex.org/I59805279","display_name":"Islamic University of Technology","ror":"https://ror.org/057gnqw22","country_code":"BD","type":"education","lineage":["https://openalex.org/I59805279"]}],"countries":["BD"],"is_corresponding":false,"raw_author_name":"S. M Mehedi Zaman","raw_affiliation_strings":["Islamic University of Technology,Department of Electrical and Electronic Engineering,Gazipur,Bangladesh,1704"],"affiliations":[{"raw_affiliation_string":"Islamic University of Technology,Department of Electrical and Electronic Engineering,Gazipur,Bangladesh,1704","institution_ids":["https://openalex.org/I59805279"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5014921097"],"corresponding_institution_ids":["https://openalex.org/I59805279"],"apc_list":null,"apc_paid":null,"fwci":0.4909,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.62654028,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"2775","issue":null,"first_page":"6534","last_page":"6539"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9995999932289124,"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"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9908999800682068,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9868000149726868,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7935727834701538},{"id":"https://openalex.org/keywords/malware","display_name":"Malware","score":0.7321411371231079},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.729885458946228},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6380070447921753},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6235290765762329},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5934714674949646},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.5271092057228088},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.47250068187713623},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32605260610580444},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.09302693605422974}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7935727834701538},{"id":"https://openalex.org/C541664917","wikidata":"https://www.wikidata.org/wiki/Q14001","display_name":"Malware","level":2,"score":0.7321411371231079},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.729885458946228},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6380070447921753},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6235290765762329},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5934714674949646},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.5271092057228088},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.47250068187713623},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32605260610580444},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.09302693605422974}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata55660.2022.10020393","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/bigdata55660.2022.10020393","pdf_url":null,"source":{"id":"https://openalex.org/S4363607709","display_name":"2022 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W2011622220","https://openalex.org/W2075522393","https://openalex.org/W2102148524","https://openalex.org/W2163563074","https://openalex.org/W2166023715","https://openalex.org/W2755577605","https://openalex.org/W2766123777","https://openalex.org/W2767134515","https://openalex.org/W2768552973","https://openalex.org/W2790429699","https://openalex.org/W2804769055","https://openalex.org/W2886064601","https://openalex.org/W2902901670","https://openalex.org/W2921740467","https://openalex.org/W2949676527","https://openalex.org/W2952171869","https://openalex.org/W2962880130","https://openalex.org/W2963563709","https://openalex.org/W2987201163","https://openalex.org/W2999309192","https://openalex.org/W3081125651","https://openalex.org/W3120369609","https://openalex.org/W3165924587","https://openalex.org/W3184338512","https://openalex.org/W3193870278","https://openalex.org/W3213204049","https://openalex.org/W4200579912","https://openalex.org/W4250664506","https://openalex.org/W4288296172","https://openalex.org/W4293192048","https://openalex.org/W6756556786","https://openalex.org/W6763828714","https://openalex.org/W6765451912","https://openalex.org/W6789214268","https://openalex.org/W7008839282","https://openalex.org/W7062580218"],"related_works":["https://openalex.org/W2602382373","https://openalex.org/W3003615511","https://openalex.org/W3198113463","https://openalex.org/W4285827128","https://openalex.org/W2787698406","https://openalex.org/W2963844355","https://openalex.org/W4361251046","https://openalex.org/W3082059448","https://openalex.org/W3095116576","https://openalex.org/W98577079"],"abstract_inverted_index":{"Cyberspace":[0],"occupies":[1],"a":[2,41,130],"large":[3],"portion":[4],"of":[5,11,68,74,87,163,175,193,210],"people\u2019s":[6],"life":[7],"in":[8,108,121,229,239],"the":[9,78,84,150,154,161,164,191,208,215,232],"age":[10],"modern":[12],"technology,":[13],"and":[14,44,54,57,120,179,185,204],"while":[15],"there":[16,24,60],"are":[17,25,61],"those":[18,27],"who":[19,28],"utilize":[20],"it":[21,45,90],"for":[22,129,153,181],"good,":[23],"also":[26],"do":[29],"not.":[30],"Malware":[31],"is":[32,70,127,170,238],"an":[33,143],"application":[34],"whose":[35],"construction":[36],"was":[37],"not":[38],"motivated":[39],"by":[40],"benign":[42],"goal":[43],"can":[46,80],"harm,":[47],"steal,":[48],"or":[49],"even":[50],"alter":[51],"personal":[52],"information":[53],"secure":[55],"applications":[56],"software.":[58],"Thus,":[59],"numerous":[62],"techniques":[63,244],"to":[64,71,91,96,111,123,148,219,225,241],"avoid":[65],"malware,":[66],"one":[67],"which":[69,125],"develop":[72],"samples":[73],"malware":[75,114],"so":[76],"that":[77],"system":[79],"be":[81,137],"updated":[82],"with":[83,173],"growing":[85],"number":[86],"malwares,":[88],"allowing":[89],"recognize":[92],"when":[93],"malwares":[94],"attempt":[95],"enter.":[97],"The":[98],"Generative":[99],"Adversarial":[100],"Network":[101],"(GAN)":[102],"sampling":[103,243],"technique":[104,218],"has":[105],"been":[106],"used":[107],"this":[109,159,211,221,230],"study":[110,140,233],"generate":[112],"new":[113],"samples.":[115],"GANs":[116],"have":[117],"multiple":[118],"variants,":[119],"order":[122],"determine":[124,149],"variant":[126],"optimal":[128,151],"given":[131],"dataset":[132,155],"sample,":[133],"their":[134],"parameters":[135],"must":[136],"modified.":[138],"This":[139],"employs":[141,214],"Optuna,":[142],"autonomous":[144],"hyperparameter":[145],"tuning":[146],"algorithm,":[147],"settings":[152],"under":[156],"consideration.":[157],"In":[158,223],"study,":[160],"architecture":[162],"Optuna":[165],"Optimized":[166],"GAN":[167,237],"(OOG)":[168],"method":[169],"shown,":[171],"along":[172],"scores":[174],"98.06%,":[176],"99.00%,":[177],"97.23%,":[178],"98.04%":[180],"accuracy,":[182],"precision,":[183],"recall":[184],"f1":[186],"score":[187],"respectively.":[188],"After":[189],"tweaking":[190],"hyperparameters":[192],"five":[194],"supervised":[195],"boosting":[196],"algorithms,":[197],"XGBoost,":[198],"LightGBM,":[199],"CatBoost,":[200],"Extra":[201],"Trees":[202],"Classifier,":[203,207],"Gradient":[205],"Boosting":[206],"methodology":[209],"paper":[212],"additionally":[213],"weighted":[216],"ensemble":[217],"acquire":[220],"result.":[222],"addition":[224],"comparing":[226],"existing":[227],"efforts":[228],"domain,":[231],"demonstrates":[234],"how":[235],"promising":[236],"comparison":[240],"other":[242],"such":[245],"as":[246],"SMOTE.":[247]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2025-12-24T23:09:58.560324","created_date":"2025-10-10T00:00:00"}
