{"id":"https://openalex.org/W2583678697","doi":"https://doi.org/10.1109/bigdata.2016.7841008","title":"Android malware detection with weak ground truth data","display_name":"Android malware detection with weak ground truth data","publication_year":2016,"publication_date":"2016-12-01","ids":{"openalex":"https://openalex.org/W2583678697","doi":"https://doi.org/10.1109/bigdata.2016.7841008","mag":"2583678697"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata.2016.7841008","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2016.7841008","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 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/A5085711960","display_name":"Jordan DeLoach","orcid":null},"institutions":[{"id":"https://openalex.org/I189590672","display_name":"Kansas State University","ror":"https://ror.org/05p1j8758","country_code":"US","type":"education","lineage":["https://openalex.org/I189590672"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jordan DeLoach","raw_affiliation_strings":["Department of Computer Science, Kansas State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Kansas State University","institution_ids":["https://openalex.org/I189590672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067341711","display_name":"Doina Caragea","orcid":"https://orcid.org/0000-0002-6440-0914"},"institutions":[{"id":"https://openalex.org/I189590672","display_name":"Kansas State University","ror":"https://ror.org/05p1j8758","country_code":"US","type":"education","lineage":["https://openalex.org/I189590672"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Doina Caragea","raw_affiliation_strings":["Department of Computer Science, Kansas State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Kansas State University","institution_ids":["https://openalex.org/I189590672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113810433","display_name":"Xinming Ou","orcid":"https://orcid.org/0009-0007-2501-7991"},"institutions":[{"id":"https://openalex.org/I2613432","display_name":"University of South Florida","ror":"https://ror.org/032db5x82","country_code":"US","type":"education","lineage":["https://openalex.org/I2613432"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xinming Ou","raw_affiliation_strings":["Deptartment of Computer Science and Engineering, University of South Florida"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Deptartment of Computer Science and Engineering, University of South Florida","institution_ids":["https://openalex.org/I2613432"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.021,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.79097039,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"16","issue":null,"first_page":"3457","last_page":"3464"},"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":0.9925000071525574,"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/T10743","display_name":"Software Testing and Debugging Techniques","score":0.9886000156402588,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/android-malware","display_name":"Android malware","score":0.8490603566169739},{"id":"https://openalex.org/keywords/malware","display_name":"Malware","score":0.7852883338928223},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7714383602142334},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.7552732229232788},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6428478956222534},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6208429932594299},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5975154638290405},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.5354604125022888},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5194187164306641},{"id":"https://openalex.org/keywords/android","display_name":"Android (operating system)","score":0.4756816625595093},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.22106385231018066}],"concepts":[{"id":"https://openalex.org/C2989133298","wikidata":"https://www.wikidata.org/wiki/Q94","display_name":"Android malware","level":3,"score":0.8490603566169739},{"id":"https://openalex.org/C541664917","wikidata":"https://www.wikidata.org/wiki/Q14001","display_name":"Malware","level":2,"score":0.7852883338928223},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7714383602142334},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.7552732229232788},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6428478956222534},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6208429932594299},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5975154638290405},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.5354604125022888},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5194187164306641},{"id":"https://openalex.org/C557433098","wikidata":"https://www.wikidata.org/wiki/Q94","display_name":"Android (operating system)","level":2,"score":0.4756816625595093},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.22106385231018066},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata.2016.7841008","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2016.7841008","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.6600000262260437}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320310131","display_name":"University of Kansas","ror":"https://ror.org/001tmjg57"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1445387515","https://openalex.org/W1454815643","https://openalex.org/W1503398984","https://openalex.org/W1616720564","https://openalex.org/W1659144702","https://openalex.org/W1973403081","https://openalex.org/W1976526581","https://openalex.org/W1987510309","https://openalex.org/W2000159976","https://openalex.org/W2048679005","https://openalex.org/W2091540464","https://openalex.org/W2122672392","https://openalex.org/W2125011234","https://openalex.org/W2141416357","https://openalex.org/W2141554582","https://openalex.org/W2168103835","https://openalex.org/W2220697891","https://openalex.org/W2270414365","https://openalex.org/W2298229910","https://openalex.org/W2502723504","https://openalex.org/W2559490865","https://openalex.org/W6628387306","https://openalex.org/W6628532452","https://openalex.org/W6689078042","https://openalex.org/W6730636351"],"related_works":["https://openalex.org/W2945522736","https://openalex.org/W3012546138","https://openalex.org/W2964088652","https://openalex.org/W4225292389","https://openalex.org/W4353031795","https://openalex.org/W3114980949","https://openalex.org/W4210772651","https://openalex.org/W4316659894","https://openalex.org/W4384301457","https://openalex.org/W3105429705"],"abstract_inverted_index":{"For":[0],"Android":[1,63],"malware":[2,64,98],"detection,":[3],"precise":[4,103],"ground":[5,19,80],"truth":[6,20,81],"is":[7,55,70,100,116,127,183],"a":[8,45,67,97,105,124,141,184],"rare":[9],"commodity.":[10],"As":[11],"security":[12],"knowledge":[13],"evolves,":[14],"what":[15],"may":[16,26],"be":[17,36,111,121],"considered":[18,31],"at":[21],"one":[22],"moment":[23],"in":[24,41,66,82],"time":[25],"change,":[27],"and":[28,78,154],"apps":[29],"once":[30],"benign":[32,106,125,129,162],"turn":[33],"out":[34],"to":[35,47,75,149,170],"malicious.":[37],"The":[38],"inevitable":[39],"noise":[40],"data":[42,92],"labels":[43,93],"poses":[44],"challenge":[46],"creating":[48],"effective":[49],"machine":[50],"learning":[51,60],"models.":[52],"Our":[53],"work":[54],"focused":[56],"on":[57,136],"approaches":[58],"for":[59,62,173],"classifiers":[61],"detection":[65],"manner":[68],"that":[69,90,113,123,146],"methodologically":[71],"sound":[72],"with":[73],"regard":[74],"the":[76,83,88],"uncertain":[77],"ever-changing":[79],"problem":[84],"space.":[85],"We":[86,164],"leverage":[87,140],"fact":[89],"although":[91],"are":[94,194],"unavoidably":[95],"noisy,":[96],"label":[99],"much":[101],"more":[102],"than":[104],"label.":[107],"While":[108],"you":[109,118],"can":[110,119],"confident":[112],"an":[114,132],"app":[115,126,175],"malicious,":[117],"never":[120],"certain":[122],"really":[128],"or":[130],"just":[131],"undetected":[133],"malware.":[134],"Based":[135],"this":[137],"insight,":[138],"we":[139],"modified":[142],"Logistic":[143,168],"Regression":[144,169],"classifier":[145],"allows":[147],"us":[148],"learn":[150],"from":[151],"only":[152],"positive":[153,188],"unlabeled":[155],"data,":[156,190],"without":[157],"making":[158],"any":[159],"assumptions":[160],"about":[161],"labels.":[163],"find":[165],"Label":[166],"Regularized":[167],"perform":[171],"well":[172,178],"noisy":[174],"datasets,":[176],"as":[177,179],"datasets":[180],"where":[181],"there":[182],"limited":[185],"amount":[186],"of":[187,192,196],"labeled":[189],"both":[191],"which":[193],"representative":[195],"real-world":[197],"situations.":[198]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}