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We devise a method based on a non-deterministic finite state machine to perform approximate pattern-matching, using a look-ahead mechanism implemented through a concept similar to that of a sliding window, and using threshold-based similarity checking at every state in the automaton. We introduce and formalize our approach, discuss the challenges we faced and then test it in a real-world environment. The experimental results obtained showed a significant speed-up of our approach, as compared to the classic similarity measures used commonly in such scenarios.<\/jats:p>","DOI":"10.1093\/jigpal\/jzae016","type":"journal-article","created":{"date-parts":[[2024,3,20]],"date-time":"2024-03-20T12:17:24Z","timestamp":1710937044000},"page":"210-223","source":"Crossref","is-referenced-by-count":0,"title":["Realtime polymorphic malicious behavior detection in blockchain-based smart contracts"],"prefix":"10.1093","volume":"32","author":[{"given":"Darius","family":"Gali\u015e","sequence":"first","affiliation":[{"name":"Faculty of Mathematics and Informatics , West University of Timi\u015foara, Timi\u015foara 300223, Romania, darius.galis@e-uvt.ro"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ciprian","family":"Pungil\u0102","sequence":"additional","affiliation":[{"name":"Faculty of Mathematics and Informatics , West University of Timi\u015foara, Timi\u015foara 300223, 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