{"id":"https://openalex.org/W3048726132","doi":"https://doi.org/10.1109/tc.2020.3015584","title":"MTHAEL: Cross-Architecture IoT Malware Detection Based on Neural Network Advanced Ensemble Learning","display_name":"MTHAEL: Cross-Architecture IoT Malware Detection Based on Neural Network Advanced Ensemble Learning","publication_year":2020,"publication_date":"2020-08-11","ids":{"openalex":"https://openalex.org/W3048726132","doi":"https://doi.org/10.1109/tc.2020.3015584","mag":"3048726132"},"language":"en","primary_location":{"id":"doi:10.1109/tc.2020.3015584","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tc.2020.3015584","pdf_url":null,"source":{"id":"https://openalex.org/S157670870","display_name":"IEEE Transactions on Computers","issn_l":"0018-9340","issn":["0018-9340","0016-9340","1557-9956","2326-3814"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Computers","raw_type":"journal-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/A5048806635","display_name":"Danish Vasan","orcid":"https://orcid.org/0000-0002-7693-1042"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Danish Vasan","raw_affiliation_strings":["School of Software, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-7693-1042","affiliations":[{"raw_affiliation_string":"School of Software, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018409592","display_name":"Mamoun Alazab","orcid":"https://orcid.org/0000-0002-1928-3704"},"institutions":[{"id":"https://openalex.org/I29894533","display_name":"Charles Darwin University","ror":"https://ror.org/048zcaj52","country_code":"AU","type":"education","lineage":["https://openalex.org/I29894533"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Mamoun Alazab","raw_affiliation_strings":["College of Engineering, IT & Environment, Charles Darwin University, Casuarina, NT, Australia"],"raw_orcid":"https://orcid.org/0000-0002-1928-3704","affiliations":[{"raw_affiliation_string":"College of Engineering, IT & Environment, Charles Darwin University, Casuarina, NT, Australia","institution_ids":["https://openalex.org/I29894533"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072259792","display_name":"Sitalakshmi Venkatraman","orcid":"https://orcid.org/0000-0002-2772-133X"},"institutions":[{"id":"https://openalex.org/I4403386716","display_name":"Melbourne Polytechnic","ror":"https://ror.org/04cq7wg91","country_code":null,"type":"education","lineage":["https://openalex.org/I4403386716"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Sitalakshmi Venkatraman","raw_affiliation_strings":["Information Technology, Melbourne Polytechnic, Preston, VIC, Australia"],"raw_orcid":"https://orcid.org/0000-0002-2772-133X","affiliations":[{"raw_affiliation_string":"Information Technology, Melbourne Polytechnic, Preston, VIC, Australia","institution_ids":["https://openalex.org/I4403386716"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054801104","display_name":"Junaid Akram","orcid":"https://orcid.org/0000-0003-1752-6124"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junaid Akram","raw_affiliation_strings":["School of Software, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-1752-6124","affiliations":[{"raw_affiliation_string":"School of Software, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101460210","display_name":"Zheng Qin","orcid":"https://orcid.org/0000-0002-7090-7869"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zheng Qin","raw_affiliation_strings":["School of Software, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-7090-7869","affiliations":[{"raw_affiliation_string":"School of Software, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":7.5716,"has_fulltext":false,"cited_by_count":104,"citation_normalized_percentile":{"value":0.98255657,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"69","issue":"11","first_page":"1654","last_page":"1667"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9991999864578247,"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":0.9944999814033508,"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/computer-science","display_name":"Computer science","score":0.8571794033050537},{"id":"https://openalex.org/keywords/malware","display_name":"Malware","score":0.6860488653182983},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5946298837661743},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.5461550354957581},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5411277413368225},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5364319682121277},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.49088865518569946},{"id":"https://openalex.org/keywords/arm-architecture","display_name":"ARM architecture","score":0.4532630443572998},{"id":"https://openalex.org/keywords/network-architecture","display_name":"Network architecture","score":0.4503903090953827},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4486149847507477},{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.4275969862937927},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.42129674553871155},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.4068794846534729},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.36862385272979736},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.19107681512832642},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.17442774772644043}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8571794033050537},{"id":"https://openalex.org/C541664917","wikidata":"https://www.wikidata.org/wiki/Q14001","display_name":"Malware","level":2,"score":0.6860488653182983},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5946298837661743},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.5461550354957581},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5411277413368225},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5364319682121277},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.49088865518569946},{"id":"https://openalex.org/C26771161","wikidata":"https://www.wikidata.org/wiki/Q16980","display_name":"ARM architecture","level":2,"score":0.4532630443572998},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.4503903090953827},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4486149847507477},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.4275969862937927},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.42129674553871155},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.4068794846534729},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.36862385272979736},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.19107681512832642},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.17442774772644043},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tc.2020.3015584","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tc.2020.3015584","pdf_url":null,"source":{"id":"https://openalex.org/S157670870","display_name":"IEEE Transactions on Computers","issn_l":"0018-9340","issn":["0018-9340","0016-9340","1557-9956","2326-3814"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Computers","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.5600000023841858}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":85,"referenced_works":["https://openalex.org/W95765562","https://openalex.org/W200681053","https://openalex.org/W581956982","https://openalex.org/W1479972308","https://openalex.org/W1482612322","https://openalex.org/W1506806321","https://openalex.org/W1545528966","https://openalex.org/W1562646198","https://openalex.org/W1666731339","https://openalex.org/W1806610636","https://openalex.org/W1893133781","https://openalex.org/W1973403081","https://openalex.org/W1981221397","https://openalex.org/W1982505813","https://openalex.org/W1984109827","https://openalex.org/W1984306555","https://openalex.org/W2000052253","https://openalex.org/W2003059838","https://openalex.org/W2009033060","https://openalex.org/W2025173435","https://openalex.org/W2029122708","https://openalex.org/W2031254140","https://openalex.org/W2031958382","https://openalex.org/W2034938003","https://openalex.org/W2042638791","https://openalex.org/W2054632425","https://openalex.org/W2079215333","https://openalex.org/W2080157505","https://openalex.org/W2097117768","https://openalex.org/W2099958966","https://openalex.org/W2103333826","https://openalex.org/W2105103777","https://openalex.org/W2115062372","https://openalex.org/W2119046642","https://openalex.org/W2133693888","https://openalex.org/W2137693329","https://openalex.org/W2147710616","https://openalex.org/W2150188172","https://openalex.org/W2163605009","https://openalex.org/W2170197386","https://openalex.org/W2173213060","https://openalex.org/W2194775991","https://openalex.org/W2259959024","https://openalex.org/W2360903897","https://openalex.org/W2397347223","https://openalex.org/W2474414057","https://openalex.org/W2507351359","https://openalex.org/W2508317201","https://openalex.org/W2564186131","https://openalex.org/W2612123163","https://openalex.org/W2617931713","https://openalex.org/W2732916693","https://openalex.org/W2733765803","https://openalex.org/W2734719707","https://openalex.org/W2737879662","https://openalex.org/W2745390745","https://openalex.org/W2747715470","https://openalex.org/W2765186819","https://openalex.org/W2774161712","https://openalex.org/W2791879367","https://openalex.org/W2792450155","https://openalex.org/W2792657554","https://openalex.org/W2801888526","https://openalex.org/W2884861143","https://openalex.org/W2887944710","https://openalex.org/W2902662365","https://openalex.org/W2913493033","https://openalex.org/W2914719353","https://openalex.org/W2931858311","https://openalex.org/W2946525659","https://openalex.org/W2950754826","https://openalex.org/W2963265635","https://openalex.org/W2963973118","https://openalex.org/W3123969097","https://openalex.org/W6603786617","https://openalex.org/W6608206699","https://openalex.org/W6616837769","https://openalex.org/W6630259505","https://openalex.org/W6633713445","https://openalex.org/W6646316834","https://openalex.org/W6657621473","https://openalex.org/W6679901780","https://openalex.org/W6684191040","https://openalex.org/W6746323147","https://openalex.org/W6759211943"],"related_works":["https://openalex.org/W4238897586","https://openalex.org/W435179959","https://openalex.org/W2619091065","https://openalex.org/W2341842940","https://openalex.org/W1490753184","https://openalex.org/W2284465472","https://openalex.org/W2291782699","https://openalex.org/W1993948687","https://openalex.org/W2059640416","https://openalex.org/W2329895846"],"abstract_inverted_index":{"The":[0],"complexity,":[1],"sophistication,":[2],"and":[3,11,17,45,78,87,111,131,150],"impact":[4],"of":[5,40,53,68,147],"malware":[6,23,59,174],"evolve":[7],"with":[8,83,103,141,176],"industrial":[9],"revolution":[10],"technology":[12],"advancements.":[13],"This":[14],"article":[15],"discusses":[16],"proposes":[18],"a":[19,142],"robust":[20],"cross-architecture":[21,145,172],"IoT":[22,58,94,144,173,187],"threat":[24],"hunting":[25],"model":[26,36],"based":[27],"on":[28,92],"advanced":[29],"ensemble":[30,39],"learning":[31],"(MTHAEL).":[32],"Our":[33,135],"unique":[34],"MTHAEL":[35,64,137,166],"using":[37],"stacked":[38],"heterogeneous":[41],"feature":[42],"selection":[43],"algorithms":[44],"state-of-the-art":[46],"neural":[47,75,80],"networks":[48],"to":[49,120,184],"learn":[50],"different":[51,93,104,115],"levels":[52],"semantic":[54],"features":[55],"demonstrates":[56],"enhanced":[57],"detection":[60,175],"than":[61],"existing":[62],"approaches.":[63],"is":[65,98,138],"the":[66,101,122],"first":[67],"its":[69],"kind":[70],"that":[71],"effectively":[72],"optimizes":[73],"recurrent":[74],"network":[76,81],"(RNN)":[77],"convolutional":[79],"(CNN)":[82],"high":[84],"classification":[85,155],"accuracy":[86,156],"consistently":[88],"low":[89,177],"computational":[90,178],"overheads":[91,179],"architectures.":[95],"Cross-architecture":[96],"benchmarking":[97],"performed":[99],"during":[100],"training":[102],"architectures":[105,117],"such":[106],"as":[107],"ARM,":[108],"Intel80386,":[109],"MIPS,":[110],"MIPS+Intel80386":[112],"individually.":[113],"Two":[114],"hardware":[116],"were":[118],"employed":[119],"analyze":[121],"architecture":[123,159],"overhead,":[124],"namely":[125],"Raspberry":[126],"Pi":[127],"4":[128],"(ARM-based":[129],"architecture)":[130],"Core-i5":[132],"(Intel-based":[133],"architecture).":[134],"proposed":[136],"evaluated":[139],"comprehensively":[140],"large":[143],"dataset":[146],"21,137":[148],"samples":[149],"has":[151,167],"achieved":[152],"99.98":[153],"percent":[154],"for":[157,171],"ARM":[158],"samples,":[160],"surpassing":[161],"prior":[162],"related":[163],"works.":[164],"Overall,":[165],"demonstrated":[168],"practical":[169],"suitability":[170],"requiring":[180],"only":[181],"0.32":[182],"seconds":[183],"detect":[185],"Any":[186],"malware.":[188]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":20},{"year":2024,"cited_by_count":30},{"year":2023,"cited_by_count":25},{"year":2022,"cited_by_count":13},{"year":2021,"cited_by_count":13}],"updated_date":"2026-07-10T07:45:09.275182","created_date":"2025-10-10T00:00:00"}