{"id":"https://openalex.org/W4416962083","doi":"https://doi.org/10.1109/icumt67815.2025.11268719","title":"Unveiling Ransomware: Sequence Alignment and Deep Learning for Early Detection","display_name":"Unveiling Ransomware: Sequence Alignment and Deep Learning for Early Detection","publication_year":2025,"publication_date":"2025-11-03","ids":{"openalex":"https://openalex.org/W4416962083","doi":"https://doi.org/10.1109/icumt67815.2025.11268719"},"language":null,"primary_location":{"id":"doi:10.1109/icumt67815.2025.11268719","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icumt67815.2025.11268719","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 17th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT)","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/A5093419873","display_name":"Pavel Novak","orcid":"https://orcid.org/0009-0000-5488-2190"},"institutions":[{"id":"https://openalex.org/I21449261","display_name":"Masaryk University","ror":"https://ror.org/02j46qs45","country_code":"CZ","type":"education","lineage":["https://openalex.org/I21449261"]}],"countries":["CZ"],"is_corresponding":true,"raw_author_name":"Pavel Novak","raw_affiliation_strings":["Masaryk University,Faculty of Informatics,Brno,Czechia"],"affiliations":[{"raw_affiliation_string":"Masaryk University,Faculty of Informatics,Brno,Czechia","institution_ids":["https://openalex.org/I21449261"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018939391","display_name":"V\u00e1clav Oujezsk\u00fd","orcid":"https://orcid.org/0000-0001-7629-6299"},"institutions":[{"id":"https://openalex.org/I21449261","display_name":"Masaryk University","ror":"https://ror.org/02j46qs45","country_code":"CZ","type":"education","lineage":["https://openalex.org/I21449261"]}],"countries":["CZ"],"is_corresponding":false,"raw_author_name":"Vaclav Oujezsky","raw_affiliation_strings":["Masaryk University,Faculty of Informatics,Brno,Czechia"],"affiliations":[{"raw_affiliation_string":"Masaryk University,Faculty of Informatics,Brno,Czechia","institution_ids":["https://openalex.org/I21449261"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5093419873"],"corresponding_institution_ids":["https://openalex.org/I21449261"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.49052643,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"52","last_page":"61"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9807000160217285,"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":0.9807000160217285,"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/T11644","display_name":"Spam and Phishing Detection","score":0.0034000000450760126,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.002899999963119626,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/ransomware","display_name":"Ransomware","score":0.8172000050544739},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6859999895095825},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4781000018119812},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.46129998564720154},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.4230000078678131},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.3862000107765198},{"id":"https://openalex.org/keywords/intrusion-detection-system","display_name":"Intrusion detection system","score":0.32820001244544983},{"id":"https://openalex.org/keywords/trace","display_name":"TRACE (psycholinguistics)","score":0.32739999890327454},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.32359999418258667}],"concepts":[{"id":"https://openalex.org/C2777667771","wikidata":"https://www.wikidata.org/wiki/Q926331","display_name":"Ransomware","level":3,"score":0.8172000050544739},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7333999872207642},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6919000148773193},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6859999895095825},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.49000000953674316},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4781000018119812},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4706000089645386},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.46129998564720154},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.4230000078678131},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.3862000107765198},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.32820001244544983},{"id":"https://openalex.org/C75291252","wikidata":"https://www.wikidata.org/wiki/Q1315756","display_name":"TRACE (psycholinguistics)","level":2,"score":0.32739999890327454},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.32359999418258667},{"id":"https://openalex.org/C88626702","wikidata":"https://www.wikidata.org/wiki/Q1128903","display_name":"Continuation","level":2,"score":0.3160000145435333},{"id":"https://openalex.org/C541664917","wikidata":"https://www.wikidata.org/wiki/Q14001","display_name":"Malware","level":2,"score":0.31130000948905945},{"id":"https://openalex.org/C182590292","wikidata":"https://www.wikidata.org/wiki/Q989632","display_name":"Network security","level":2,"score":0.2971999943256378},{"id":"https://openalex.org/C40506919","wikidata":"https://www.wikidata.org/wiki/Q7452469","display_name":"Sequence learning","level":2,"score":0.2903999984264374},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.28929999470710754},{"id":"https://openalex.org/C149490388","wikidata":"https://www.wikidata.org/wiki/Q1718507","display_name":"Sequential Pattern Mining","level":2,"score":0.2867000102996826},{"id":"https://openalex.org/C151201525","wikidata":"https://www.wikidata.org/wiki/Q177239","display_name":"Limit (mathematics)","level":2,"score":0.2856999933719635},{"id":"https://openalex.org/C68859911","wikidata":"https://www.wikidata.org/wiki/Q1503724","display_name":"Pattern matching","level":2,"score":0.2752000093460083},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.258899986743927},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.25529998540878296},{"id":"https://openalex.org/C2780741293","wikidata":"https://www.wikidata.org/wiki/Q4818019","display_name":"Attack patterns","level":3,"score":0.25380000472068787},{"id":"https://openalex.org/C187191949","wikidata":"https://www.wikidata.org/wiki/Q1138496","display_name":"Profiling (computer programming)","level":2,"score":0.2508000135421753}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icumt67815.2025.11268719","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icumt67815.2025.11268719","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 17th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1573526548","https://openalex.org/W1577394698","https://openalex.org/W1972243012","https://openalex.org/W2029195137","https://openalex.org/W2069143585","https://openalex.org/W2074231493","https://openalex.org/W2087064593","https://openalex.org/W2765174411","https://openalex.org/W3001630589","https://openalex.org/W3014902384","https://openalex.org/W3157814027","https://openalex.org/W3181247433","https://openalex.org/W3183350623","https://openalex.org/W4232115236","https://openalex.org/W4284990077","https://openalex.org/W4293191407","https://openalex.org/W4384129390","https://openalex.org/W4385245566","https://openalex.org/W4400302572","https://openalex.org/W4401359976","https://openalex.org/W4405450843"],"related_works":[],"abstract_inverted_index":{"Ransomware":[0],"poses":[1],"a":[2,57,141],"significant":[3],"and":[4,15,17,55,65,71,122,160],"evolving":[5],"threat":[6],"to":[7,24,43,91,111,135],"modern":[8],"information":[9],"systems,":[10],"often":[11],"causing":[12],"data":[13],"loss":[14],"financial":[16],"reputation":[18],"damage.":[19],"Traditional":[20],"detection":[21,64,121],"mechanisms":[22],"tend":[23],"focus":[25],"either":[26],"on":[27,33,140],"known":[28],"indicators":[29],"of":[30,82,108,115,151,166],"compromise":[31],"or":[32,46],"overly":[34],"specific":[35],"behavioral":[36,96],"patterns,":[37],"which":[38],"can":[39],"limit":[40],"their":[41],"ability":[42],"detect":[44,92],"novel":[45,58],"stealthy":[47],"variants.":[48],"In":[49,102],"this":[50],"paper,":[51],"we":[52,77,104],"propose,":[53],"test,":[54],"evaluate":[56],"method":[59],"for":[60],"early-stage":[61],"ransomware":[62,143,167],"infection":[63],"prediction":[66],"using":[67],"sequence":[68,74,87],"alignment":[69,88],"techniques":[70],"deep":[72],"learning-based":[73],"modeling.":[75],"Specifically,":[76],"present":[78],"an":[79],"improved":[80],"version":[81],"the":[83,106,113,148,164],"well-known":[84],"NeedlemanWunsch":[85],"global":[86],"algorithm":[89],"tailored":[90],"partially":[93],"matching":[94],"suspicious":[95],"patterns":[97],"within":[98],"network":[99,144],"traffic":[100,145],"flows.":[101],"parallel,":[103],"explore":[105],"use":[107],"transformer":[109],"models":[110],"predict":[112],"continuation":[114],"these":[116],"event":[117,132],"sequences,":[118],"enabling":[119],"earlier":[120],"response.":[123],"Our":[124],"approach":[125],"is":[126],"inspired":[127],"by":[128],"bioinformatics":[129],"methodologies,":[130],"treating":[131],"sequences":[133,159],"analogous":[134],"DNA":[136],"analysis.":[137],"Experiments":[138],"conducted":[139],"real-world":[142],"dataset":[146],"demonstrate":[147],"promising":[149],"results":[150],"our":[152],"method,":[153],"both":[154],"in":[155,161],"aligning":[156],"noisy,":[157],"interleaved":[158],"accurately":[162],"predicting":[163],"progression":[165],"behavior.":[168]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-12-03T00:00:00"}
