{"id":"https://openalex.org/W4410583903","doi":"https://doi.org/10.23919/date64628.2025.10993115","title":"Hardware-Assisted Ransomware Detection Using Automated Machine Learning","display_name":"Hardware-Assisted Ransomware Detection Using Automated Machine Learning","publication_year":2025,"publication_date":"2025-03-31","ids":{"openalex":"https://openalex.org/W4410583903","doi":"https://doi.org/10.23919/date64628.2025.10993115"},"language":"en","primary_location":{"id":"doi:10.23919/date64628.2025.10993115","is_oa":false,"landing_page_url":"https://doi.org/10.23919/date64628.2025.10993115","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 Design, Automation & Test in Europe Conference (DATE)","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/A5013876571","display_name":"Zhixin Pan","orcid":"https://orcid.org/0000-0001-9136-1730"},"institutions":[{"id":"https://openalex.org/I103163165","display_name":"Florida State University","ror":"https://ror.org/05g3dte14","country_code":"US","type":"education","lineage":["https://openalex.org/I103163165"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Zhixin Pan","raw_affiliation_strings":["Florida State University,Department of Electrical & Computer Engineering"],"affiliations":[{"raw_affiliation_string":"Florida State University,Department of Electrical & Computer Engineering","institution_ids":["https://openalex.org/I103163165"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084697185","display_name":"Ziyu Shu","orcid":"https://orcid.org/0000-0002-2530-3177"},"institutions":[{"id":"https://openalex.org/I204465549","display_name":"Washington University in St. Louis","ror":"https://ror.org/01yc7t268","country_code":"US","type":"education","lineage":["https://openalex.org/I204465549"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ziyu Shu","raw_affiliation_strings":["Washington University in St. Louis,Department of Computer Science"],"affiliations":[{"raw_affiliation_string":"Washington University in St. Louis,Department of Computer Science","institution_ids":["https://openalex.org/I204465549"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5013876571"],"corresponding_institution_ids":["https://openalex.org/I103163165"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.14857109,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9837999939918518,"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":0.9337000250816345,"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/ransomware","display_name":"Ransomware","score":0.9580624103546143},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7749350070953369},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.47814974188804626},{"id":"https://openalex.org/keywords/malware","display_name":"Malware","score":0.39363014698028564},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.35665735602378845},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3383166193962097}],"concepts":[{"id":"https://openalex.org/C2777667771","wikidata":"https://www.wikidata.org/wiki/Q926331","display_name":"Ransomware","level":3,"score":0.9580624103546143},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7749350070953369},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.47814974188804626},{"id":"https://openalex.org/C541664917","wikidata":"https://www.wikidata.org/wiki/Q14001","display_name":"Malware","level":2,"score":0.39363014698028564},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.35665735602378845},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3383166193962097}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/date64628.2025.10993115","is_oa":false,"landing_page_url":"https://doi.org/10.23919/date64628.2025.10993115","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 Design, Automation & Test in Europe Conference (DATE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W2255466643","https://openalex.org/W2775237336","https://openalex.org/W2779814706","https://openalex.org/W2899124034","https://openalex.org/W2951172748","https://openalex.org/W2953056235","https://openalex.org/W3000953536","https://openalex.org/W3028767182","https://openalex.org/W3153302004","https://openalex.org/W3205163562","https://openalex.org/W4237807841","https://openalex.org/W4316690373","https://openalex.org/W4379879883","https://openalex.org/W4386266016","https://openalex.org/W4386988695","https://openalex.org/W4387821098","https://openalex.org/W4390673835","https://openalex.org/W6686742002"],"related_works":["https://openalex.org/W3201228709","https://openalex.org/W2922354075","https://openalex.org/W4389157351","https://openalex.org/W4232561318","https://openalex.org/W3202245533","https://openalex.org/W4253977752","https://openalex.org/W2942879794","https://openalex.org/W2964829536","https://openalex.org/W2904586340","https://openalex.org/W3120595989"],"abstract_inverted_index":{"Ransomware":[0],"has":[1],"emerged":[2],"as":[3],"a":[4,43,88,101],"severe":[5],"privacy":[6],"threat,":[7],"leading":[8],"to":[9,58,76,92,107,131,139,143],"significant":[10],"financial":[11],"and":[12,23,33,133],"data":[13],"losses":[14],"worldwide.":[15],"Traditional":[16],"detection":[17,22,60,94,127,135],"methods,":[18],"including":[19],"static":[20,82],"signature-based":[21],"dynamic":[24,90],"behavior-based":[25],"analysis,":[26],"have":[27],"shown":[28],"limitations":[29],"in":[30],"effectively":[31],"identifying":[32],"mitigating":[34],"ever-evolving":[35],"ransomware":[36],"attacks.":[37],"In":[38],"this":[39,63],"paper,":[40],"we":[41],"present":[42],"machine":[44,112],"learning-based":[45],"framework":[46],"that":[47,122],"integrates":[48],"both":[49],"software-level":[50],"scanning":[51],"along":[52,86],"with":[53,87],"hardware-level":[54],"microprocessor":[55],"activity":[56],"monitoring":[57],"enhance":[59],"performance.":[61],"Specifically,":[62],"paper":[64],"offers":[65],"three":[66],"important":[67],"contributions.":[68],"(1)":[69],"The":[70,97],"proposed":[71,98,124],"method":[72,99,125],"incorporates":[73],"adversarial":[74],"training":[75],"address":[77],"the":[78,109],"weaknesses":[79],"of":[80,111],"conventional":[81],"analysis":[83,91],"against":[84],"obfuscation,":[85],"hardware-assisted":[89],"reduce":[93],"latency.":[95],"(2)":[96],"employs":[100],"neural":[102],"architecture":[103],"search":[104],"(NAS)":[105],"algorithm":[106],"automate":[108],"optimization":[110],"learning":[113],"models,":[114],"significantly":[115],"boosting":[116],"generalizability.":[117],"(3)":[118],"Experimental":[119],"results":[120],"demonstrates":[121],"our":[123],"improves":[126],"accuracy":[128],"by":[129,137],"up":[130,138],"10.2%":[132],"reduces":[134],"latency":[136],"4.8x":[140],"speedup":[141],"compared":[142],"existing":[144],"approaches.":[145]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}