A metrics-based recommendation strategy for code obfuscation

Yuqiang Xiao; Yunfei Guo; Yawen Wang; Shumin Huo; Huanruo Li; Benwei He

doi:10.1117/12.2653040

10 November 2022 A metrics-based recommendation strategy for code obfuscation

Yuqiang Xiao, Yunfei Guo, Yawen Wang, Shumin Huo, Huanruo Li, Benwei He

Proceedings Volume 12331, International Conference on Mechanisms and Robotics (ICMAR 2022); 123313N (2022) https://doi.org/10.1117/12.2653040
Event: International Conference on Mechanisms and Robotics (ICMAR 2022), 2022, Zhuhai, China

Abstract

Obfuscation is a method of endogenous security commonly used to thwart software vulnerabilities exploitation and protect important properties such as intellectual property rights, software algorithms and user privacy. Numerous obfuscation techniques and products have been developed after decades of research while it is hard for users to are easy to figure out how to apply these obfuscation rules properly or if a program is obfuscated sufficiently. To solve this problem, this paper proposes a recommendation strategy for code obfuscation based on comprehensive metrics, providing a new scope for obfuscation development and applications. The strategy was implemented and verified on obfuscators and a suit of program benchmarks, demonstrating the strategy could obfuscate programs sufficiently with cost reduced by 30% within five obfuscation rules in average.

Citation Download Citation

Yuqiang Xiao, Yunfei Guo, Yawen Wang, Shumin Huo, Huanruo Li, and Benwei He "A metrics-based recommendation strategy for code obfuscation", Proc. SPIE 12331, International Conference on Mechanisms and Robotics (ICMAR 2022), 123313N (10 November 2022); https://doi.org/10.1117/12.2653040

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