Malicious JavaScript Detection Based on AST Analysis and Key Feature Re-sampling in Realistic Environments-Reference-Cited by-同舟云学术

Malicious JavaScript Detection Based on AST Analysis and Key Feature Re-sampling in Realistic Environments

Published:2023 Issue: Volume: Page:225-241
ISSN:0302-9743
Container-title:Codes, Cryptology and Information Security
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Author:

Phung Ngoc Minh^ORCID,Mimura Mamoru^ORCID

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-33017-9_15

Reference28 articles.

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3. Choi, J., Choi, C., You, I., Kim, P.: Polymorphic malicious JavaScript code detection for APT attack defence. J. Univers. Comput. Sci. 21, 369–383 (2015)

4. Dewald, A., Holz, T., Freiling, F.: ADSandbox: sandboxing JavaScript to fight malicious websites. In: SAC 2010 (2010)

5. Esprima: Documentation on using esprima vol 4.0, December 2022. https://docs.esprima.org/en/4.0/

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