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- W4234480284 abstract "This paper proposes a method for evaluating the artificiality of protected code by means of an N-gram model. The proposed artificiality metric helps us measure the stealth of the protected code, that is, the degree to which protected code can be distinguished from unprotected code. In a case study, we use the proposed method to evaluate the artificiality of programs that are transformed by well-known obfuscation techniques. The results show that static obfuscating transformations (e.g., Control flow flattening) have little effect on artificiality. However, dynamic obfuscating transformations (e.g., Code encryption), or a technique that inserts junk code fragments into the program, tend to increase the artificiality, which may have a significant impact on the stealth of the code." @default.
- W4234480284 created "2022-05-12" @default.
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- W4234480284 date "2015-05-01" @default.
- W4234480284 modified "2023-09-26" @default.
- W4234480284 title "Code Artificiality: A Metric for the Code Stealth Based on an N-Gram Model" @default.
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- W4234480284 doi "https://doi.org/10.1109/spro.2015.14" @default.
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