{"id":"https://openalex.org/W3011265823","doi":"https://doi.org/10.1109/milcom47813.2019.9020790","title":"Detection of Prevalent Malware Families with Deep Learning","display_name":"Detection of Prevalent Malware Families with Deep Learning","publication_year":2019,"publication_date":"2019-11-01","ids":{"openalex":"https://openalex.org/W3011265823","doi":"https://doi.org/10.1109/milcom47813.2019.9020790","mag":"3011265823"},"language":"en","primary_location":{"id":"doi:10.1109/milcom47813.2019.9020790","is_oa":false,"landing_page_url":"https://doi.org/10.1109/milcom47813.2019.9020790","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"MILCOM 2019 - 2019 IEEE Military Communications Conference (MILCOM)","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/A5059859993","display_name":"Jack W. Stokes","orcid":null},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jack W. Stokes","raw_affiliation_strings":["Microsoft Research, Redmond, Washington, USA"],"affiliations":[{"raw_affiliation_string":"Microsoft Research, Redmond, Washington, USA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060280412","display_name":"Christian Seifert","orcid":"https://orcid.org/0000-0001-9182-8687"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Christian Seifert","raw_affiliation_strings":["Microsoft Corporation, Redmond, Washington, USA"],"affiliations":[{"raw_affiliation_string":"Microsoft Corporation, Redmond, Washington, USA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018892689","display_name":"Jerry Li","orcid":null},"institutions":[{"id":"https://openalex.org/I4210142583","display_name":"Snap (United States)","ror":"https://ror.org/04dgkhg68","country_code":"US","type":"company","lineage":["https://openalex.org/I4210142583"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jerry Li","raw_affiliation_strings":["Snap Corporation, Seattle, WA, USA"],"affiliations":[{"raw_affiliation_string":"Snap Corporation, Seattle, WA, USA","institution_ids":["https://openalex.org/I4210142583"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084726762","display_name":"Nizar Hejazi","orcid":null},"institutions":[{"id":"https://openalex.org/I2946016260","display_name":"Uber AI (United States)","ror":"https://ror.org/05vm0ed18","country_code":"US","type":"company","lineage":["https://openalex.org/I2946016260"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nizar Hejazi","raw_affiliation_strings":["Uber Corporation, Seattle, WA, USA"],"affiliations":[{"raw_affiliation_string":"Uber Corporation, Seattle, WA, USA","institution_ids":["https://openalex.org/I2946016260"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5059859993"],"corresponding_institution_ids":["https://openalex.org/I1290206253"],"apc_list":null,"apc_paid":null,"fwci":0.6634,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.70774518,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"7","issue":null,"first_page":"1","last_page":"8"},"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":0.9990000128746033,"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":0.9911999702453613,"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":0.8181055784225464},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.665237307548523},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4943876266479492},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.47634032368659973},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.4487919211387634}],"concepts":[{"id":"https://openalex.org/C541664917","wikidata":"https://www.wikidata.org/wiki/Q14001","display_name":"Malware","level":2,"score":0.8181055784225464},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.665237307548523},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4943876266479492},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.47634032368659973},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.4487919211387634}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/milcom47813.2019.9020790","is_oa":false,"landing_page_url":"https://doi.org/10.1109/milcom47813.2019.9020790","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"MILCOM 2019 - 2019 IEEE Military Communications Conference (MILCOM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.6700000166893005,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W7103708","https://openalex.org/W78162143","https://openalex.org/W117149299","https://openalex.org/W191656338","https://openalex.org/W200681053","https://openalex.org/W1487207002","https://openalex.org/W1507388815","https://openalex.org/W1545528966","https://openalex.org/W1559833478","https://openalex.org/W1591082683","https://openalex.org/W1827212170","https://openalex.org/W1893133781","https://openalex.org/W1910686388","https://openalex.org/W1943233084","https://openalex.org/W1966948031","https://openalex.org/W1967981049","https://openalex.org/W2018175892","https://openalex.org/W2084979543","https://openalex.org/W2115175195","https://openalex.org/W2120297918","https://openalex.org/W2127589108","https://openalex.org/W2136189984","https://openalex.org/W2176830056","https://openalex.org/W2187089797","https://openalex.org/W2473839235","https://openalex.org/W4212863985","https://openalex.org/W4213009331","https://openalex.org/W4299585995","https://openalex.org/W4300601563","https://openalex.org/W6600275301","https://openalex.org/W6629167580","https://openalex.org/W6633282783","https://openalex.org/W6638623425","https://openalex.org/W6639864006","https://openalex.org/W6677522032","https://openalex.org/W6677743974","https://openalex.org/W6685576885","https://openalex.org/W6721021859"],"related_works":["https://openalex.org/W2259219744","https://openalex.org/W1936417930","https://openalex.org/W1827256152","https://openalex.org/W3042673639","https://openalex.org/W2623682848","https://openalex.org/W2731899572","https://openalex.org/W3016595359","https://openalex.org/W3205304540","https://openalex.org/W2968586400","https://openalex.org/W4309968681"],"abstract_inverted_index":{"Attackers":[0],"evolve":[1],"their":[2,31,60],"malware":[3,57,130,199],"over":[4],"time":[5],"in":[6,121,148,159],"order":[7],"to":[8,19,30,39,77,100,151,180,196],"evade":[9],"detection,":[10],"and":[11,44,59,79,93],"the":[12,23,63,109,126,156,160],"rate":[13,165],"of":[14,25,55,113,129],"change":[15,35],"varies":[16],"from":[17],"family":[18,20],"depending":[21],"on":[22],"amount":[24],"resources":[26],"these":[27,49,84,114],"groups":[28],"devote":[29],"\u201cproduct\u201d.":[32],"This":[33],"rapid":[34],"forces":[36],"anti-malware":[37],"companies":[38,52,73],"also":[40],"direct":[41],"much":[42],"human":[43],"automated":[45],"effort":[46],"towards":[47],"combatting":[48],"threats.":[50],"These":[51],"track":[53],"thousands":[54],"distinct":[56],"families":[58,66],"variants,":[61],"but":[62],"most":[64],"prevalent":[65,86],"are":[67,119],"often":[68],"particularly":[69],"problematic.":[70],"While":[71],"some":[72],"employ":[74],"many":[75],"analysts":[76],"investigate":[78],"create":[80],"new":[81,96],"signatures":[82],"for":[83,155,166,182],"highly":[85],"families,":[87],"we":[88],"take":[89],"a":[90,95,102,122,137,183],"different":[91],"approach":[92],"propose":[94],"deep":[97],"learning":[98],"system":[99,135],"learn":[101,152],"semantic":[103],"feature":[104,161],"embedding":[105,154],"which":[106,118,142,187],"better":[107],"discriminates":[108],"files":[110,117],"within":[111],"each":[112],"families.":[115],"Identifying":[116],"close":[120],"metric":[123],"space":[124],"is":[125,177],"key":[127],"aspect":[128],"clustering":[131],"systems.":[132],"The":[133,163],"DeepSim":[134],"employs":[136],"Siamese":[138],"Neural":[139],"Network":[140],"(SNN),":[141],"has":[143,188],"previously":[144,193],"shown":[145],"promising":[146],"results":[147],"other":[149],"domains,":[150],"this":[153],"cosine":[157],"distance":[158],"space.":[162],"error":[164],"K-Nearest":[167],"Neighbor":[168],"classification":[169],"using":[170],"DeepSim's":[171],"SNN":[172],"with":[173],"two":[174],"hidden":[175],"layers":[176],"0.011%":[178],"compared":[179],"0.42%":[181],"Jaccard":[184],"Index-based":[185],"baseline":[186],"been":[189],"used":[190],"by":[191],"several":[192],"proposed":[194],"systems":[195],"identify":[197],"similar":[198],"files.":[200]},"counts_by_year":[{"year":2022,"cited_by_count":2},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}