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- W2725713545 abstract "In order to ensure the normal operation and security of the software, this paper presents an abnormal behavior state recognition system based on Hidden Markov model, using the local regularity of the trace of the system call to extract the intrinsic sequence pattern, and construct the normal behavior model through the HMM algorithm. This system is capable of establishing the system call model during normal operation and judge whether the software is running normally by the matching between the actual system call and the normal model. Experiments show that, compared with only using system call sequence information of classical hidden Markov method, the method of training time is only 10% of the traditional method, and can obtain lower false positive rate and false negative rate." @default.
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- W2725713545 date "2017-07-05" @default.
- W2725713545 modified "2023-09-27" @default.
- W2725713545 title "Software Abnormal Behavior Detection Based on Hidden Markov Model" @default.
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- W2725713545 doi "https://doi.org/10.1007/978-3-319-61542-4_94" @default.
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