{"id":"https://openalex.org/W4281795618","doi":"https://doi.org/10.1145/3526241.3530825","title":"CAD-FSL: Code-Aware Data Generation based Few-Shot Learning for Efficient Malware Detection","display_name":"CAD-FSL: Code-Aware Data Generation based Few-Shot Learning for Efficient Malware Detection","publication_year":2022,"publication_date":"2022-06-02","ids":{"openalex":"https://openalex.org/W4281795618","doi":"https://doi.org/10.1145/3526241.3530825"},"language":"en","primary_location":{"id":"doi:10.1145/3526241.3530825","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3526241.3530825","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3526241.3530825","source":{"id":"https://openalex.org/S4363608736","display_name":"Proceedings of the Great Lakes Symposium on VLSI 2022","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Great Lakes Symposium on VLSI 2022","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3526241.3530825","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5004945691","display_name":"Sreenitha Kasarapu","orcid":"https://orcid.org/0000-0002-9974-1348"},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sreenitha Kasarapu","raw_affiliation_strings":["George Mason University, Fairfax, VA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"George Mason University, Fairfax, VA, USA","institution_ids":["https://openalex.org/I162714631"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081814168","display_name":"Sanket Shukla","orcid":"https://orcid.org/0000-0002-1861-249X"},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sanket Shukla","raw_affiliation_strings":["George Mason University, Fairfax, VA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"George Mason University, Fairfax, VA, USA","institution_ids":["https://openalex.org/I162714631"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051223866","display_name":"Rakibul Hassan","orcid":"https://orcid.org/0000-0002-9516-8361"},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rakibul Hassan","raw_affiliation_strings":["George Mason University, Fairfax, VA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"George Mason University, Fairfax, VA, USA","institution_ids":["https://openalex.org/I162714631"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060036961","display_name":"Avesta Sasan","orcid":"https://orcid.org/0000-0002-4052-8075"},"institutions":[{"id":"https://openalex.org/I84218800","display_name":"University of California, Davis","ror":"https://ror.org/05rrcem69","country_code":"US","type":"education","lineage":["https://openalex.org/I84218800"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Avesta Sasan","raw_affiliation_strings":["University of California Davis, Davis, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California Davis, Davis, CA, USA","institution_ids":["https://openalex.org/I84218800"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047382437","display_name":"Houman Homayoun","orcid":"https://orcid.org/0000-0001-8904-4699"},"institutions":[{"id":"https://openalex.org/I84218800","display_name":"University of California, Davis","ror":"https://ror.org/05rrcem69","country_code":"US","type":"education","lineage":["https://openalex.org/I84218800"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Houman Homayoun","raw_affiliation_strings":["University of California, Davis, Davis, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California, Davis, Davis, CA, USA","institution_ids":["https://openalex.org/I84218800"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110615104","display_name":"Sai Manoj PD","orcid":null},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sai Manoj PD","raw_affiliation_strings":["George Mason University, Fairfax, VA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"George Mason University, Fairfax, VA, USA","institution_ids":["https://openalex.org/I162714631"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.3314,"has_fulltext":true,"cited_by_count":12,"citation_normalized_percentile":{"value":0.82845452,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"507","last_page":"512"},"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/T10743","display_name":"Software Testing and Debugging Techniques","score":0.9927999973297119,"subfield":{"id":"https://openalex.org/subfields/1712","display_name":"Software"},"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":0.991100013256073,"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/malware","display_name":"Malware","score":0.9615583419799805},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.853374719619751},{"id":"https://openalex.org/keywords/cryptovirology","display_name":"Cryptovirology","score":0.6622153520584106},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.5681383013725281},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5534218549728394},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5345629453659058},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.47099536657333374},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4540002644062042},{"id":"https://openalex.org/keywords/minification","display_name":"Minification","score":0.4217785894870758},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3430059552192688},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.31679022312164307}],"concepts":[{"id":"https://openalex.org/C541664917","wikidata":"https://www.wikidata.org/wiki/Q14001","display_name":"Malware","level":2,"score":0.9615583419799805},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.853374719619751},{"id":"https://openalex.org/C84525096","wikidata":"https://www.wikidata.org/wiki/Q3506050","display_name":"Cryptovirology","level":3,"score":0.6622153520584106},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.5681383013725281},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5534218549728394},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5345629453659058},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.47099536657333374},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4540002644062042},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.4217785894870758},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3430059552192688},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.31679022312164307},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3526241.3530825","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3526241.3530825","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3526241.3530825","source":{"id":"https://openalex.org/S4363608736","display_name":"Proceedings of the Great Lakes Symposium on VLSI 2022","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Great Lakes Symposium on VLSI 2022","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3526241.3530825","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3526241.3530825","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3526241.3530825","source":{"id":"https://openalex.org/S4363608736","display_name":"Proceedings of the Great Lakes Symposium on VLSI 2022","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Great Lakes Symposium on VLSI 2022","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4281795618.pdf","grobid_xml":"https://content.openalex.org/works/W4281795618.grobid-xml"},"referenced_works_count":9,"referenced_works":["https://openalex.org/W2012132268","https://openalex.org/W2215444025","https://openalex.org/W2412229656","https://openalex.org/W2544988394","https://openalex.org/W2750780705","https://openalex.org/W2766576889","https://openalex.org/W3006334803","https://openalex.org/W3215200159","https://openalex.org/W4235228933"],"related_works":["https://openalex.org/W4256304280","https://openalex.org/W4249009605","https://openalex.org/W2900526031","https://openalex.org/W2395100307","https://openalex.org/W2909615516","https://openalex.org/W3183826413","https://openalex.org/W4243179955","https://openalex.org/W3205001643","https://openalex.org/W2557742076","https://openalex.org/W2968504645"],"abstract_inverted_index":{"One":[0],"of":[1,63,71,97],"the":[2,34,39,61,69,98,110,115,124,134,139,145,159],"pivotal":[3],"security":[4],"threats":[5],"for":[6,25,49,76,102],"embedded":[7],"computing":[8],"systems":[9],"is":[10,131,172],"malicious":[11],"softwarea.k.a":[12],"malware.":[13],"With":[14],"efficiency":[15],"and":[16,46,51,122],"efficacy,":[17],"Machine":[18],"Learning":[19],"(ML)":[20],"has":[21],"been":[22],"widely":[23],"adopted":[24],"malware":[26,47,55,65,73,101,104,120,130,147,167],"detection":[27,62],"in":[28],"recent":[29],"times.":[30],"Despite":[31],"being":[32],"efficient,":[33],"existing":[35],"techniques":[36],"require":[37],"updating":[38],"ML":[40],"model":[41,140],"frequently":[42],"with":[43,158,168,179],"newer":[44],"benign":[45],"samples":[48,66,74,96,112],"training":[50,135,177,183],"modeling":[52],"an":[53],"efficient":[54,77,103],"detector.":[56],"Furthermore,":[57],"such":[58,81],"constraints":[59],"limit":[60],"emerging":[64,146],"due":[67],"to":[68,137],"lack":[70],"sufficient":[72],"required":[75],"training.":[78],"To":[79],"address":[80],"concerns,":[82],"we":[83,165],"introduce":[84],"a":[85],"code-aware":[86],"data":[87],"generation-based":[88],"few-shot":[89],"learning":[90],"technique.":[91],"CAD-FSL":[92],"generates":[93],"multiple":[94],"mutated":[95],"limitedly":[99,116,181],"seen":[100,117],"detection.":[105],"Loss":[106],"minimization":[107],"ensures":[108],"that":[109,141,157],"generated":[111],"closely":[113],"mimic":[114],"malware,":[118],"restore":[119],"functionality":[121],"mitigate":[123],"impractical":[125],"samples.":[126],"Such":[127],"developed":[128],"synthetic":[129],"incorporated":[132],"into":[133],"set":[136],"formulate":[138],"can":[142],"efficiently":[143],"detect":[144,166],"despite":[148],"having":[149],"limited":[150],"(few-shot)":[151],"exposure.":[152],"The":[153],"experimental":[154],"results":[155],"demonstrate":[156],"proposed":[160],"\"Code-Aware":[161],"Data":[162],"Generation\"":[163],"technique,":[164],"90%":[169],"accuracy,":[170],"which":[171],"approximately":[173],"9%":[174],"higher":[175],"while":[176],"classifiers":[178],"only":[180],"available":[182],"data.":[184]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
