Simplifying state machine models with sequence alignment for anomaly detection

Zhang, S.X.

Simplifying state machine models with sequence alignment for anomaly detection

Master thesis (2024)

Authors

S.X. Zhang Electrical Engineering, Mathematics and Computer Science

Contributors

S.E. Verwer Algorithmics - (mentor)

A. Panichella Software Engineering - (graduation committee member)

Faculty

Electrical Engineering, Mathematics and Computer Science

Sequence alignment Automata State machine learning Behavioral differencing Finte state automata Deterministic finite state automata Needleman-wunsch Software logs

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Published Date

30-08-2024

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Files

TUD_Report-3.pdf

(pdf | 2.84 Mb)

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