Fast Preprocessing by Suffix Arrays for Managing Byte n-grams to Detect Malware Subspecies by Machine Learning

Author:

Kita Kouhei1,Uda Ryuya1

Affiliation:

1. Tokyo University of Technology

Publisher

Information Processing Society of Japan

Reference38 articles.

1. [1] Hsu, C., Shih, F., Wang, C. and Shieh, S.W.: Divergence Detector: A Fine-Grained Approach to Detecting VM-Awareness Malware, Proc. 7th International Conference on Software Security and Reliability, pp.80-89 (2013).

2. [2] Ye, Y., Chen, L., Wang, D. and Li, T.: SBMDS: An Interpretable String Based Malware Detection System Using SVM Ensemble with Bagging, Journal in Computer Virology, Vol.5, No.4, pp.283-293 (2009).

3. [3] Tanabe, R., Ueno, W., Hoshizawa, Y., Saito, T., Kasama, T., Inoue, D., Yoshioka, K. and Matsumoto, T.: Evaluation of Security Appliance against Customized Malware, IPSJ Journal, Vol.60, No.9, pp.1466-1476 (2019) (Japanese).

4. [4] The Mystery of the Encrypted Gauss Payloads, available from <https://securelist.com/the-mystery-of-the-encrypted-gauss-payload-5/33561/> (accessed 2023-08-10).

5. [5] Ishimaru, S.: Why Corrupted (?) Samples in Recent APT? - Case of Japan and Taiwan, available from <https://hitcon.org/2016/pacific/0composition/pdf/1201/1201%20R1%201500%20why%20corrupted%20samples%20in%20recent%20apt.pdf> (accessed 2023-08-10).

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