{"id":"https://openalex.org/W3214977413","doi":"https://doi.org/10.1186/s42400-021-00102-9","title":"LSGAN-AT: enhancing malware detector robustness against adversarial examples","display_name":"LSGAN-AT: enhancing malware detector robustness against adversarial examples","publication_year":2021,"publication_date":"2021-12-01","ids":{"openalex":"https://openalex.org/W3214977413","doi":"https://doi.org/10.1186/s42400-021-00102-9","mag":"3214977413"},"language":"en","primary_location":{"id":"doi:10.1186/s42400-021-00102-9","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s42400-021-00102-9","pdf_url":"https://cybersecurity.springeropen.com/counter/pdf/10.1186/s42400-021-00102-9","source":{"id":"https://openalex.org/S3035238565","display_name":"Cybersecurity","issn_l":"2523-3246","issn":["2523-3246"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Cybersecurity","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://cybersecurity.springeropen.com/counter/pdf/10.1186/s42400-021-00102-9","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100420034","display_name":"Jianhua Wang","orcid":"https://orcid.org/0000-0002-2773-3429"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jianhua Wang","raw_affiliation_strings":["Beijing Key Laboratory of Security and Privacy in Intelligent Transportation, Beijing Jiaotong University, 3 Shangyuancun, Beijing, 100044, China"],"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Security and Privacy in Intelligent Transportation, Beijing Jiaotong University, 3 Shangyuancun, Beijing, 100044, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024597522","display_name":"Xiaolin Chang","orcid":"https://orcid.org/0000-0002-2975-8857"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaolin Chang","raw_affiliation_strings":["Beijing Key Laboratory of Security and Privacy in Intelligent Transportation, Beijing Jiaotong University, 3 Shangyuancun, Beijing, 100044, China"],"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Security and Privacy in Intelligent Transportation, Beijing Jiaotong University, 3 Shangyuancun, Beijing, 100044, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100706399","display_name":"Yixiang Wang","orcid":"https://orcid.org/0000-0002-2393-4127"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yixiang Wang","raw_affiliation_strings":["Beijing Key Laboratory of Security and Privacy in Intelligent Transportation, Beijing Jiaotong University, 3 Shangyuancun, Beijing, 100044, China"],"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Security and Privacy in Intelligent Transportation, Beijing Jiaotong University, 3 Shangyuancun, Beijing, 100044, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048946273","display_name":"Ricardo J. Rodr\u00edguez","orcid":"https://orcid.org/0000-0001-7982-0359"},"institutions":[{"id":"https://openalex.org/I255234318","display_name":"Universidad de Zaragoza","ror":"https://ror.org/012a91z28","country_code":"ES","type":"education","lineage":["https://openalex.org/I255234318"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Ricardo J. Rodr\u00edguez","raw_affiliation_strings":["Department of Computer Science and Systems Engineering, University of Zaragoza, Calle Mar\u00eda de Luna 1, Zaragoza, 50018, Spain"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Systems Engineering, University of Zaragoza, Calle Mar\u00eda de Luna 1, Zaragoza, 50018, Spain","institution_ids":["https://openalex.org/I255234318"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100460589","display_name":"Jianan Zhang","orcid":"https://orcid.org/0000-0003-2611-9838"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianan Zhang","raw_affiliation_strings":["Beijing Key Laboratory of Security and Privacy in Intelligent Transportation, Beijing Jiaotong University, 3 Shangyuancun, Beijing, 100044, China"],"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Security and Privacy in Intelligent Transportation, Beijing Jiaotong University, 3 Shangyuancun, Beijing, 100044, China","institution_ids":["https://openalex.org/I21193070"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100420034"],"corresponding_institution_ids":["https://openalex.org/I21193070"],"apc_list":null,"apc_paid":null,"fwci":2.9397,"has_fulltext":true,"cited_by_count":27,"citation_normalized_percentile":{"value":0.92537366,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"4","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9997000098228455,"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/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9983999729156494,"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/T12122","display_name":"Physical Unclonable Functions (PUFs) and Hardware Security","score":0.9890999794006348,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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/transferability","display_name":"Transferability","score":0.8231234550476074},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.8066009283065796},{"id":"https://openalex.org/keywords/malware","display_name":"Malware","score":0.726648211479187},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6818134784698486},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.621807336807251},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.5906537771224976},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4591708779335022},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.45540791749954224},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34464031457901},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3233930468559265},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.32271212339401245},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.1937616467475891}],"concepts":[{"id":"https://openalex.org/C61272859","wikidata":"https://www.wikidata.org/wiki/Q7834031","display_name":"Transferability","level":3,"score":0.8231234550476074},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.8066009283065796},{"id":"https://openalex.org/C541664917","wikidata":"https://www.wikidata.org/wiki/Q14001","display_name":"Malware","level":2,"score":0.726648211479187},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6818134784698486},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.621807336807251},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.5906537771224976},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4591708779335022},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45540791749954224},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34464031457901},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3233930468559265},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.32271212339401245},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.1937616467475891},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C140331021","wikidata":"https://www.wikidata.org/wiki/Q1868104","display_name":"Logit","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1186/s42400-021-00102-9","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s42400-021-00102-9","pdf_url":"https://cybersecurity.springeropen.com/counter/pdf/10.1186/s42400-021-00102-9","source":{"id":"https://openalex.org/S3035238565","display_name":"Cybersecurity","issn_l":"2523-3246","issn":["2523-3246"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Cybersecurity","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:6cd390847dbd4392914b322c5efd1529","is_oa":true,"landing_page_url":"https://doaj.org/article/6cd390847dbd4392914b322c5efd1529","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Cybersecurity, Vol 4, Iss 1, Pp 1-15 (2021)","raw_type":"article"},{"id":"pmh:oai:zaguan.unizar.es:109683","is_oa":true,"landing_page_url":"http://zaguan.unizar.es/record/109683","pdf_url":null,"source":{"id":"https://openalex.org/S4306401812","display_name":"Zaguan (University of Zaragoza Repository)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I255234318","host_organization_name":"Universidad de Zaragoza","host_organization_lineage":["https://openalex.org/I255234318"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1186/s42400-021-00102-9","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s42400-021-00102-9","pdf_url":"https://cybersecurity.springeropen.com/counter/pdf/10.1186/s42400-021-00102-9","source":{"id":"https://openalex.org/S3035238565","display_name":"Cybersecurity","issn_l":"2523-3246","issn":["2523-3246"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Cybersecurity","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3214977413.pdf","grobid_xml":"https://content.openalex.org/works/W3214977413.grobid-xml"},"referenced_works_count":39,"referenced_works":["https://openalex.org/W1985663105","https://openalex.org/W2037109870","https://openalex.org/W2095577883","https://openalex.org/W2101234009","https://openalex.org/W2110889728","https://openalex.org/W2122672392","https://openalex.org/W2125011234","https://openalex.org/W2131523719","https://openalex.org/W2180612164","https://openalex.org/W2215444025","https://openalex.org/W2407313496","https://openalex.org/W2550924701","https://openalex.org/W2593414223","https://openalex.org/W2610321374","https://openalex.org/W2744095836","https://openalex.org/W2765811365","https://openalex.org/W2773446523","https://openalex.org/W2780061022","https://openalex.org/W2930249865","https://openalex.org/W2943919788","https://openalex.org/W2963178695","https://openalex.org/W2963448658","https://openalex.org/W2963461515","https://openalex.org/W2964082701","https://openalex.org/W2973628901","https://openalex.org/W2974031746","https://openalex.org/W2995512646","https://openalex.org/W3026802938","https://openalex.org/W3036847733","https://openalex.org/W3040148743","https://openalex.org/W3086404086","https://openalex.org/W3089994140","https://openalex.org/W3095495550","https://openalex.org/W3104141960","https://openalex.org/W3134311463","https://openalex.org/W3168097936","https://openalex.org/W4247200422","https://openalex.org/W4312393595","https://openalex.org/W6661032068"],"related_works":["https://openalex.org/W4288055406","https://openalex.org/W3137894200","https://openalex.org/W3092178728","https://openalex.org/W4226402597","https://openalex.org/W4200630034","https://openalex.org/W3132910851","https://openalex.org/W4377864639","https://openalex.org/W2997056298","https://openalex.org/W2950864148","https://openalex.org/W2570685808"],"abstract_inverted_index":{"Abstract":[0],"Adversarial":[1,31,77],"Malware":[2,123],"Example":[3],"(AME)-based":[4],"adversarial":[5,112],"training":[6,57,113],"can":[7,88],"effectively":[8],"enhance":[9,71],"the":[10,27,42,49,130,143,150,158,161,165],"robustness":[11,28,75],"of":[12,37,51,133,137,148,160,168],"Machine":[13],"Learning":[14],"(ML)-based":[15],"malware":[16,73],"detectors":[17,141],"against":[18,76],"AME.":[19,169],"AME":[20,38,45,94,115,134],"quality":[21],"is":[22,34],"a":[23,35,64],"key":[24],"factor":[25],"to":[26,70,105,119],"enhancement.":[29],"Generative":[30],"Network":[32],"(GAN)":[33],"kind":[36],"generation":[39,46],"method,":[40],"but":[41],"existing":[43],"GAN-based":[44],"methods":[47],"have":[48],"issues":[50],"inadequate":[52],"optimization,":[53],"mode":[54],"collapse":[55],"and":[56,83,92,100,142],"instability.":[58],"In":[59],"this":[60],"paper,":[61],"we":[62],"propose":[63],"novel":[65],"approach":[66],"(denote":[67],"as":[68],"LSGAN-AT)":[69],"ML-based":[72,121],"detector":[74],"Examples,":[78],"which":[79],"includes":[80],"LSGAN":[81,86,118],"module":[82,87,110],"AT":[84,109],"module.":[85],"generate":[89,120],"more":[90],"effective":[91],"smoother":[93],"by":[95,117],"utilizing":[96],"brand-new":[97],"network":[98],"structures":[99],"Least":[101],"Square":[102],"(LS)":[103],"loss":[104],"optimize":[106],"boundary":[107],"samples.":[108],"makes":[111],"using":[114],"generated":[116,162],"Robust":[122],"Detector":[124],"(RMD).":[125],"Extensive":[126],"experiment":[127],"results":[128,155],"validate":[129],"better":[131],"transferability":[132,145],"in":[135,146,164],"terms":[136,147],"attacking":[138],"6":[139],"ML":[140],"RMD":[144,163],"resisting":[149],"MalGAN":[151],"black-box":[152],"attack.":[153],"The":[154],"also":[156],"verify":[157],"performance":[159],"recognition":[166],"rate":[167]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":4}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}