{"id":"https://openalex.org/W3030931690","doi":"https://doi.org/10.1145/3374135.3385316","title":"Comparing Performance of Malware Classification on Automated Stacking","display_name":"Comparing Performance of Malware Classification on Automated Stacking","publication_year":2020,"publication_date":"2020-04-02","ids":{"openalex":"https://openalex.org/W3030931690","doi":"https://doi.org/10.1145/3374135.3385316","mag":"3030931690"},"language":"en","primary_location":{"id":"doi:10.1145/3374135.3385316","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3374135.3385316","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 ACM Southeast Conference","raw_type":"proceedings-article"},"type":"conference-paper","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/A5046997510","display_name":"Nusrat Asrafi","orcid":null},"institutions":[{"id":"https://openalex.org/I172980758","display_name":"Kennesaw State University","ror":"https://ror.org/00jeqjx33","country_code":"US","type":"education","lineage":["https://openalex.org/I172980758"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nusrat Asrafi","raw_affiliation_strings":["Kennesaw State University, Marietta, Georgia, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kennesaw State University, Marietta, Georgia, USA","institution_ids":["https://openalex.org/I172980758"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085923839","display_name":"Dan Lo","orcid":"https://orcid.org/0000-0003-4396-0370"},"institutions":[{"id":"https://openalex.org/I172980758","display_name":"Kennesaw State University","ror":"https://ror.org/00jeqjx33","country_code":"US","type":"education","lineage":["https://openalex.org/I172980758"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dan Chia-Tien Lo","raw_affiliation_strings":["Kennesaw State University, Marietta, Georgia, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kennesaw State University, Marietta, Georgia, USA","institution_ids":["https://openalex.org/I172980758"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087589295","display_name":"Reza M. Parizi","orcid":"https://orcid.org/0000-0002-0049-4296"},"institutions":[{"id":"https://openalex.org/I172980758","display_name":"Kennesaw State University","ror":"https://ror.org/00jeqjx33","country_code":"US","type":"education","lineage":["https://openalex.org/I172980758"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Reza M. Parizi","raw_affiliation_strings":["Kennesaw State University, Marietta, Georgia, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kennesaw State University, Marietta, Georgia, USA","institution_ids":["https://openalex.org/I172980758"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102950309","display_name":"Yong Shi","orcid":"https://orcid.org/0000-0003-0895-9868"},"institutions":[{"id":"https://openalex.org/I172980758","display_name":"Kennesaw State University","ror":"https://ror.org/00jeqjx33","country_code":"US","type":"education","lineage":["https://openalex.org/I172980758"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yong Shi","raw_affiliation_strings":["Kennesaw State University, Marietta, Georgia, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kennesaw State University, Marietta, Georgia, USA","institution_ids":["https://openalex.org/I172980758"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100428119","display_name":"Yu\u2010Wen Chen","orcid":"https://orcid.org/0000-0002-4335-7574"},"institutions":[{"id":"https://openalex.org/I76513827","display_name":"New York City College of Technology","ror":"https://ror.org/021a7pw18","country_code":"US","type":"education","lineage":["https://openalex.org/I76513827"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yu-Wen Chen","raw_affiliation_strings":["New York City College of Technology, Brooklyn, New York, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"New York City College of Technology, Brooklyn, New York, USA","institution_ids":["https://openalex.org/I76513827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"307","last_page":"308"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11241","display_name":"Advanced Malware Detection Techniques","score":1.0,"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":1.0,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9993000030517578,"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":0.993399977684021,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/malware","display_name":"Malware","score":0.9098490476608276},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8250964283943176},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.7209979295730591},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6960293054580688},{"id":"https://openalex.org/keywords/adaboost","display_name":"AdaBoost","score":0.648932933807373},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.5931034684181213},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4600823223590851},{"id":"https://openalex.org/keywords/statistical-classification","display_name":"Statistical classification","score":0.4557795226573944},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.43630725145339966},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.42098382115364075},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3612903952598572},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.324124276638031},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.10632464289665222}],"concepts":[{"id":"https://openalex.org/C541664917","wikidata":"https://www.wikidata.org/wiki/Q14001","display_name":"Malware","level":2,"score":0.9098490476608276},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8250964283943176},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.7209979295730591},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6960293054580688},{"id":"https://openalex.org/C141404830","wikidata":"https://www.wikidata.org/wiki/Q2823869","display_name":"AdaBoost","level":3,"score":0.648932933807373},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.5931034684181213},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4600823223590851},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.4557795226573944},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.43630725145339966},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.42098382115364075},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3612903952598572},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.324124276638031},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.10632464289665222}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3374135.3385316","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3374135.3385316","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 ACM Southeast Conference","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":6,"referenced_works":["https://openalex.org/W1995416968","https://openalex.org/W2507113366","https://openalex.org/W2947398662","https://openalex.org/W2950005521","https://openalex.org/W2982413766","https://openalex.org/W2991150929"],"related_works":["https://openalex.org/W2327035729","https://openalex.org/W2348748958","https://openalex.org/W3039673966","https://openalex.org/W2884325279","https://openalex.org/W1570592793","https://openalex.org/W1525436954","https://openalex.org/W2385662756","https://openalex.org/W2585372724","https://openalex.org/W2241444561","https://openalex.org/W1502951582"],"abstract_inverted_index":{"Stacking":[0],"in":[1,27],"machine":[2,58],"learning":[3,59],"allows":[4],"multiple":[5],"classification":[6,40],"or":[7],"regression":[8],"algorithms":[9,60],"to":[10,16,33],"work":[11],"together":[12],"with":[13,56,79],"a":[14,28,69,75],"goal":[15],"enhance":[17],"performance.":[18],"To":[19],"understand":[20],"the":[21,42,46,87],"risky":[22],"properties":[23],"of":[24,44,48],"malware":[25,36,88],"contamination":[26],"system,":[29],"it":[30],"is":[31,41,72],"important":[32],"accurately":[34],"classify":[35],"type":[37],"first.":[38],"Malware":[39],"procedure":[43],"labeling":[45],"families":[47],"malware.":[49],"In":[50],"this":[51],"paper,":[52],"we":[53],"automate":[54],"stacking":[55],"7":[57],"and":[61],"3":[62],"boosting":[63],"algorithms.":[64],"The":[65],"experimental":[66],"results":[67],"show":[68],"99.2%":[70],"accuracy":[71],"achieved":[73],"from":[74],"multilayer":[76],"perceptron":[77],"network":[78],"AdaBoost":[80],"classifier,":[81],"which":[82],"outperforms":[83],"other":[84],"models":[85],"on":[86],"API":[89],"call":[90],"dataset.":[91]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
