Reverse engineering can automatically collect the path information which has been leaked in program run-time

and then reveal the internal logics of programs. To mitigate path information leaking

this paper proposes a novel path obfuscator to combat state-of-art reverse engineering by using random forest. The difficulty of reversing the obfuscated branch is equivalent to extracting rules from random forests. Since random forests can be regarded as black-box and the categorizing process has high similarity with the behavior of path branch

so the specially trained random forest can realize the functionality of path branch. The proposed obfuscator had been deployed on six programs from SPECint-2006 benchmarks. The experimental results show that our method has significantly increased the computational cost of reverse engineering

and the introduced overhead is acceptable.