PKDGA: A Partial Knowledge-based Domain Generation Algorithm for Botnets
نویسندگان
چکیده
Domain generation algorithms (DGAs) can be categorized into three types: zero-knowledge , xmlns:xlink="http://www.w3.org/1999/xlink">partial-knowledge and xmlns:xlink="http://www.w3.org/1999/xlink">full-knowledge . While prior research merely focused on types, we characterize their anti-detection ability practicality find that DGAs present low against xmlns:xlink="http://www.w3.org/1999/xlink">detectors suffer from due to the strong assumption they are fully xmlns:xlink="http://www.w3.org/1999/xlink">detector -aware. Given these observations, propose xmlns:xlink="http://www.w3.org/1999/xlink">PKDGA a partial knowledge-based domain algorithm with high practicality. employs reinforcement learning architecture, which makes it evolve automatically based only easily-observable feedback detectors. We evaluate using comprehensive set of real-world datasets, results demonstrate reduces detection performance existing 91.7% 52.5%. further apply xmlns:xlink="http://www.w3.org/1999/xlink">Mirai malware, evaluations show proposed method is quite lightweight time-efficient.
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ژورنال
عنوان ژورنال: IEEE Transactions on Information Forensics and Security
سال: 2023
ISSN: ['1556-6013', '1556-6021']
DOI: https://doi.org/10.1109/tifs.2023.3298229